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DeepLearning.University – An Annotated Deep Learning Bibliography

This resource is partly funded by the EU research project Envisage where Memkite is a case study

Maintainer: Amund Tveit – amund@memkite.com

DeepLearning.University – Abstract

DeepLearning.University is an annotated bibliography of recent publications (2014-2015) related to Deep Learning. If you have suggestions to improvements of this bibliography please send us an email or make your changes as a pull request on the corresponding git project at https://github.com/memkite/DeepLearningBibliography

Links to Deep Learning Subtopics

[2d] [3d] [acoustic] [acoustic model] [action recognition] [action recognitionx] [action selection] [activation functions] [activity detection] [activity recognition] [adaptive] [ads] [adversarial nets] [adversarial networks] [advertising] [age estimation] [aircraft detection] [algorithm] [algorithms] [alzheimer’s] [animal identification] [applications] [approximate] [architecture] [articulatory synthesis] [asthma] [asynchronous][auto-encoder] [autoencoder] [autogression] [autonomous] [autonomously] [autoregression] [back propagation] [bacteria] [barcode detection] [batch] [batch normalization] [batchwise] [bayes] [bayesian] [behavior model] [behavior models] [belief propagation networks] [bengio] [bifurcated deep network] [big] [big data] [big-data] [bing challenge] [bioinformatics] [biologically] [biology] [bird] [blstm] [boosted] [boosting] [bootstrapping] [brain] [brain waves] [caffe] [calibration] [cancer] [car detection] [cartography] [cascade] [cell] [challenges] [character recognition] [chinese] [classification] [click-through] [cloud] [clustered] [clustering] [cnn] [coding scheme] [cognition] [cognitive] [collaborative filtering] [combinatorical optimization] [compression] [computer vision] [concept learning] [consistency] [constrained] [constructive neural networks] [content-based] [contour detection] [controller] [convex] [convex optimization] [convexity] [convnet] [convnets] [convoluational neural network] [convolutional] [convolutional network] [convolutional networks] [convolutional neural network] [convolutional neural networks] [corpora] [cortical processing] [ct] [data center] [data mining] [data-parallel] [dataset] [dcnn] [decision making] [decision tree] [deep belief nets] [deep belief network] [deep boltzmann machines] [deep convex networks] [deep learning] [deep neural network] [deep sigmoid belief networks] [deeply-supervised nets] [deformation] [deformations] [demodulation] [denoising] [depression] [depth estimation] [depth-videos] [dermatology] [devops] [diabetes] [diabetic] [diacritization] [dictionary] [dictionary extraction] [digit classification] [digit recognition] [disambiguation] [discriminative] [discriminative learning] [disease] [disjunctive] [distance functions] [distributed] [distributed system] [dnn] [domain invariance] [domain-adversarial] [drone] [dropout] [drug] [drug target detection] [economy] [edge detection] [education] [eeg] [electricity] [electricity forecast] [embedded] [emotion] [emotion detection] [encoding] [encryption] [energy] [energy efficiency] [energy efficient] [ensemble learning] [entities] [entity] [error correction] [estimation] [evaluation] [event] [event detection] [examination] [experimental] [extreme learning] [eye detection] [eye tracking] [face] [face detection] [face expression analysis] [face recognition] [facial] [factorization] [fault diagnosis] [feature] [feature discovery] [feature encoding] [feature extraction] [feature recognition] [feature representation] [feature selection] [feature tuning] [features] [filtering] [finance] [fine tuning] [fine-tuning] [fingerprint detection] [fingerprint recognition] [fisher vectors] [fmri] [food detection] [fpga] [fpga-based] [framework] [freehand] [frequency domain] [fuzzy learning] [galaxy] [game] [games] [gaussian] [generative] [generative deep learning] [genetic programming] [gesture] [gesture recognition] [go] [googlenet] [gpu] [gradient] [gradient-based] [graph] [graphical model] [graphics] [graphs] [grasping system] [hadoop] [hand pose] [handwriting recognition] [handwritten] [handwritten recognition] [hardware] [hash] [hashing] [healthcare] [hearing aid] [heart failure] [helicopter] [hessian] [hierarchical] [high-dimensional data] [hmax] [hmm] [hmm-based] [hough transform] [human behavior] [human pose] [human-level] [hyperspectral] [image classification] [image de-noising] [image parsing] [image quality] [image recognition] [image recognitionx] [image representation] [image segmentation] [imagery] [imaging] [improvisation] [indexing] [induction] [inductive bias] [information] [information retrieval] [information theory] [information-theoretic] [infrastructure] [interpolation] [invariant] [javascript] [kernel] [kernel methods] [kernels] [kickback] [labeling] [lasso] [latent structure] [lattice] [learning to rank] [lecun] [lfw] [linear model] [linear models] [log-likelihood] [logistic] [long short-term memory] [low resolution] [lstm] [machine translation] [mahout] [mammogram analysis] [manufacturing] [matrix] [max pooling] [medical] [medical records] [medicine] [memory] [memristor] [metric] [metric learning] [microblog] [mimd] [mine detection] [missing] [mobile] [monte carlo] [motion] [motion detection] [motion recognition] [mri] [multi-label] [multicore] [multimedia] [multimodal] [music] [natural language processing] [network] [network analysis] [network congestion] [networking] [neuromorphic] [neuron] [neuroscience] [newton] [noise] [noiseness] [noisy] [noisy data] [non-convex] [non-euclidian] [numerical] [numerics] [object classification] [object detection] [object localization] [object recognition] [object reconstruction] [occlusion] [occlusions] [online learning] [open source] [optimization] [optimized] [orientation estimation] [over-sampling] [overview] [pancreas] [parallel] [parallelization] [parameter] [parameter tuning] [parameters] [parsing] [part-of-speech] [pca] [pedestrian detection] [perception] [perceptron] [performance improvement] [personalize] [phoneme] [photo adjustment] [photonic] [physics] [pinterest] [plankton] [planning] [platform] [pooling] [pose] [pose recognition] [posture recognition] [pre-training] [predicting] [prediction] [predictive modelling] [predictors] [pretraining] [probabilistic] [processor] [programming language processing] [prosthetics] [proteinomics] [python] [quality] [quantum] [quantum computing] [quantum deep learning] [random field] [random fields] [random forests] [ranking] [rbm] [recommendation systems] [recommender systems] [rectified] [rectifiers] [rectifiers:] [recurrant neural networks] [recurrent] [recurrent nets] [recurrent networks] [recurrent neural networks] [regression] [regularization] [reinforcement learning] [reliability] [representation] [representation learning] [restricted boltzmann machine] [restricted boltzmann machines] [restricted bolzmann machines] [retail] [retinal images] [reverse annealing] [review] [risk minimization] [road detection] [robot] [robotics] [robust] [salient] [sampling] [sar data] [scalability] [scene classification] [scene recognition] [scheduling] [score function] [sda] [search] [security] [segmentation] [self-informed] [semantic] [semantic indexing] [semantics] [semantix indexing] [semi-supervised] [sensor data] [sensory] [sentiment] [sentiment analysis] [sequence learning] [sequence modelling] [shape classification] [shearlet transform] [sigmoid] [sign language] [signal processing] [similarity learning] [simplicity] [simulation] [singular value decomposition] [sketch recognition] [smart city] [smart homes] [smoothing] [social] [social network] [soft computing] [softmax] [software] [sosial network] [sound] [sound retrieval] [spam] [sparse] [sparseness] [sparsity] [spatial] [spatial planning] [spatially] [spatio-temporal] [spectral] [spectral classification] [speech] [speech recognition] [speech synthesis] [stability] [statistical inference] [stochastic] [stochastic gradient] [stochastic gradient descent] [stochastic optimization] [strategiesx] [structured networks] [study] [subspace analysis] [subspace learning] [summarization] [supervised] [supervised learning] [support vector machine] [support vector machines] [surrogates] [survey] [svm] [swarm optimization] [synonym extraction] [target coding] [target detection] [temporal] [temporal dependencies] [tensor] [term] [text classification] [text recognition] [texture recognition] [theano] [theory] [thermodynamics] [thin deep networks] [time series] [tongue] [tool] [tools] [topic modelling] [traffic] [traffic prediction] [traffic sign] [transcription] [transductive] [transfer learning] [tree structure] [tree structures] [trends] [twitter] [ultrasound] [una] [unsupervised] [unsupervised learning] [user authentication] [user interface] [user interfaces] [vehicle] [vehicle classification] [vehicle classificationx] [vehicle recognition][videos] [vision] [visual] [visual memory] [vocal] [voice recognition] [vowel] [weather prediction] [web mining] [web search] [web spam] [weed classification] [weld] [wind power] [word embeddings] [word segmentation] [word sense]

2D

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. Dense 3d Face Alignment from 2d Videos in Real-Time

 

3D

  1. A deep learning approach to the classification of 3D CAD models
  2. 3d object retrieval with stacked local convolutional autoencoder
  3. Deep Learning Representation using Autoencoder for 3d Shape Retrieval
  4. Local deep feature learning framework for 3d shape
  5. Human gesture recognition using three-dimensional integral imaging
  6. Indirect shape analysis for 3d shape retrieval
  7. Supervised feature learning via â„“2-norm regularized logistic regression for 3d object recognition
  8. A 3d model recognition mechanism based on deep boltzmann machines
  9. Combining heterogenous features for 3d hand-held object recognition
  10. Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images
  11. A comparison of 3d shape retrieval methods based on a large-scale benchmark supporting multimodal queries
  12. Deep Learning For Objective Quality Assessment Of 3d Images
  13. Designing Deep Networks for Surface Normal Estimation
  14. TriViews: A general framework to use 3d depth data effectively for action recognition
  15. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners
  16. C3d: Generic Features for Video Analysis
  17. Semantic Volume Segmentation with Iterative Context Integration
  18. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  19. Inferring 3d Object Pose in Rgb-d Images
  20. Dense 3d Face Alignment from 2d Videos in Real-Time
  21. Learning Descriptors for Object Recognition and 3d Pose Estimation
  22. Fitting 3d Morphable Models using Local Features
  23. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  24. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  25. Iterative 3d shape classification by online metric learning

 

Acoustic

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Improving acoustic model for English Asr System using deep neural network
  5. Deep Neural Networks for Acoustic Modeling

 

Acoustic Model

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Improving acoustic model for English Asr System using deep neural network
  4. Deep Neural Networks for Acoustic Modeling

 

Action Recognition

  1. Action Recognition Using Hierarchical Independent Subspace Analysis with Trajectory
  2. Learning spatio-temporal features for action recognition from the side of the video
  3. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  4. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  5. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  6. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach

 

Action Recognitionx

  1. TriViews: A general framework to use 3d depth data effectively for action recognition

 

Action Selection

  1. Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer

 

Activation Functions

  1. Learning Activation Functions to Improve Deep Neural Networks

 

Activity Detection

  1. Neural Networks Based Methods for Voice Activity Detection in a Multi-room Domestic Environment

 

Activity Recognition

  1. Proposal for a Deep Learning Architecture for Activity Recognition

 

Adaptive

  1. Adaptive Road Detection via Context-aware Label Transfer
  2. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  3. Dynamic Feature-Adaptive Subdivision
  4. Deep Neural Programs for Adaptive Control in Cyber-Physical Systems
  5. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

Ads

  1. On optimizing machine learning workloads via kernel fusion

 

Adversarial Nets

  1. Conditional generative adversarial nets for convolutional face generation

 

Adversarial Networks

  1. Conditional Generative Adversarial Nets

 

Advertising

  1. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis

 

Age Estimation

  1. Age Estimation by Multi-scale Convolutional Network

 

Aircraft Detection

  1. Aircraft Detection by Deep Convolutional Neural Networks

 

Algorithm

  1. Mean-normalized stochastic gradient for large-scale deep learning
  2. Exponentially Increasing the Capacity-to-Computation Ratio for Conditional Computation in Deep Learning
  3. Deep process neural network for temporal deep learning
  4. On the Equivalence Between Deep NADE and Generative Stochastic Networks
  5. Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks
  6. Manifold Regularized Deep Neural Networks
  7. Deep Epitomic Convolutional Neural Networks
  8. A Winner-Take-All Method for Training Sparse Convolutional Autoencoders
  9. Analyzing noise in autoencoders and deep networks
  10. CNN: Single-label to Multi-label
  11. A comparison of dropout and weight decay for regularizing deep neural networks
  12. Feed Forward Pre-training for Recurrent Neural Network Language Models
  13. Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
  14. On the saddle point problem for non-convex optimization
  15. Dropout: A Simple Way to Prevent Neural Networks from Overfitting
  16. Reweighted Wake-Sleep
  17. Learning Separable Filters
  18. Karush-Kuhn-Tucker meets David Hubel and Torsten Weisel through Gabriel Kreiman and Andrew Ng: A connection between highlights of constrained convex..
  19. Learning Deep Representations via Extreme Learning Machines
  20. Recognizing human activity in smart home using deep learning algorithm
  21. Going Deeper with Convolutions
  22. Parallel batch pattern training algorithm for deep neural network
  23. Improved Perception-Based Spiking Neuron Learning Rule for Real-Time User Authentication
  24. Unsupervised Domain Adaptation by Backpropagation
  25. Zero-Shot Learning with Structured Embeddings
  26. Autoencoder Trees
  27. Classifying Gray-scale Sar Images: Adeep Learning Approach
  28. Maximum Reconstruction Probability Training Of Restricted Boltzmann Machines With Auxiliary Function Approach
  29. Deep Sequential Neural Network
  30. Finding quasi core with simulated stacked neural networks
  31. Understanding Locally Competitive Networks
  32. Accuracy evaluation of deep belief networks with fixed-point arithmetic
  33. On the Computational Efficiency of Training Neural Networks
  34. SimNets: A Generalization of Convolutional Networks
  35. Semantics of Visual Discrimination
  36. Temporal Coherence in Energy-based Deep Learning Machines for Action Recognition
  37. The Potential Energy of an Autoencoder
  38. Enhanced Higgs to $\ tau^+\ tau^-$ Searches with Deep Learning
  39. A Simple Stochastic Algorithm for Structural Features Learning
  40. Meta-parameter free unsupervised sparse feature learning
  41. On the Link Between Gaussian Homotopy Continuation and Convex Envelopes
  42. Coarse-to-Fine Minimization of Some Common Nonconvexities
  43. A Method For Extracting Information From The Web Using Deep Learning Algorithm
  44. Adaptive Information-Theoretical Feature Selection for Pattern Classification
  45. Stacked Extreme Learning Machines
  46. The atoms of neural computation
  47. On The Dynamical Nature Of Computation
  48. Greedy Approaches to Semi-Supervised Subspace Learning
  49. Low Rank Tensor Manifold Learning
  50. Random feedback weights support learning in deep neural networks
  51. Temporal Dropout of Changes Approach to Convolutional Learning of Spatio-Temporal Features
  52. A new algorithm on variable-rate convolutional broadcast for network coding in cyclic networks
  53. Identification and Elucidation of Expression Quantitative Trait Loci (eQTL) and their regulating mechanisms using Decodive Deep Learning
  54. Dynamic Background Learning through Deep Auto-encoder Networks
  55. Bimmer: a novel algorithm for detecting differential Dna methylation regions from MBDCap-seq data
  56. Set-label modeling and deep metric learning on person re-identification
  57. Stacked Quantizers for Compositional Vector Compression
  58. SelfieBoost: A Boosting Algorithm for Deep Learning
  59. Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
  60. Supervised non-negative matrix factorization for audio source separation
  61. Multiscale Centerline Detection
  62. A Convex Formulation for Spectral Shrunk Clustering
  63. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates
  64. The Loss Surface of Multilayer Networks
  65. Cross-Modal Learning via Pairwise Constraints
  66. An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
  67. Support Vector-Based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification
  68. Online Bandit Learning for a Special Class of Non-convex Losses
  69. A twice face recognition algorithm
  70. Implementation of Evolutionary Algorithms for Deep Architectures
  71. Stochastic Descent Analysis of Representation Learning Algorithms
  72. Preliminary evaluation of hyperopt algorithms on HPOLib
  73. Class Margins: Learning to (Un) Learn
  74. Accelerated gradient temporal difference learning algorithms
  75. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  76. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  77. Exploring Latent Structure in Data: Algorithms and Implementations
  78. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  79. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  80. Cascade object detection with complementary features and algorithms
  81. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
  82. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification

 

Algorithms

  1. Margin Perceptrons for Graphs

 

Alzheimer’S

  1. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  2. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Animal Identification

  1. Automatic Animal Species Identification Based on Camera Trapping Data

 

Applications

  1. Mariana: Tencent Deep Learning Platform and its Applications
  2. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects
  3. Traffic Flow Prediction With Big Data: A Deep Learning Approach
  4. Non-parametric Bayesian Learning with Deep Learning Structure and Its Applications in Wireless Networks
  5. Log-Linear Models, Extensions and Applications
  6. Machine Learning for Medical Applications
  7. Extreme learning machines: new trends and applications
  8. Extreme learning machines: new trends and applications
  9. An Overview of Color Name Applications in Computer Vision
  10. Deep learning applications and challenges in big data analytics
  11. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  12. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  13. Multithreshold Entropy Linear Classifier: Theory and Applications

 

Approximate

  1. Single image super-resolution by approximated Heaviside functions
  2. Optimizing Neural Networks with Kronecker-factored Approximate Curvature

 

Architecture

  1. Supervised deep learning with auxiliary networks
  2. Analysis of Deep Convolutional Neural Network Architectures
  3. Return of the Devil in the Details: Delving Deep into Convolutional Nets
  4. Learning Deep and Wide: A Spectral Method for Learning Deep Networks
  5. A Generalized Scalable Software Architecture for Analyzing Temporally Structured Big Data in the Cloud
  6. A Fully Pipelined FPGA Architecture of a Factored Restricted Boltzmann Machine Artificial Neural Network
  7. Project Adam: Building an Efficient and Scalable Deep Learning Training System
  8. Unsupervised Feature Learning For Bootleg Detection Using Deep Learning Architectures
  9. Proposal for a Deep Learning Architecture for Activity Recognition
  10. Unisense: A Unified and Sustainable Sensing and Transport Architecture for Large Scale and Heterogeneous Sensor Networks
  11. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
  12. Da-ccd: A novel action representation by deep architecture of local depth feature
  13. Review of Advances in Neural Networks: Neural Design Technology Stack
  14. An Adaptive Stacked Denoising Auto-Encoder Architecture for Human Action Recognition
  15. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  16. Towards Deep Neural Network Architectures Robust to Adversarial Examples
  17. Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology
  18. Implementation of Evolutionary Algorithms for Deep Architectures
  19. Visual Scene Representations: Scaling and Occlusion in Convolutional Architectures
  20. Obtaining Cross-modal Similarity Metric with Deep Neural Architecture
  21. Hierarchical reinforcement learning in a biologically plausible neural architecture
  22. Scene Recognition by Manifold Regularized Deep Learning Architecture
  23. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  24. Universal Memory Architectures for Autonomous Machines
  25. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  26. A Minimal Architecture for General Cognition
  27. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  28. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

Articulatory Synthesis

  1. Data driven articulatory synthesis with deep neural networks

 

Asthma

  1. Predicting Likelihood of Hospitalization with Subset-Filtered Emerging Patterns

 

Asynchronous

  1. Distributed Asynchronous Optimization of Convolutional Neural Networks
  2. Asynchronous stochastic optimization for sequence training of deep neural networks
  3. Distributed Asynchronous Optimization of Convolutional Neural Networks
  4. Contour Motion Estimation for Asynchronous Event-Driven Cameras
  5. Improving training time of deep neural networkwith asynchronous averaged stochastic gradient descent

 

Audio

  1. Improved audio features for large-scale multimedia event detection
  2. Single Channel Source Separation with General Stochastic Networks
  3. Chord Recognition with Stacked Denoising Autoencoders
  4. A Deep Neural Network Approach to Automatic Birdsong Recognition
  5. Unsupervised Feature Learning for Audio Classification using Convolutional Deep Belief Networks
  6. Automated intelligent system for sound signalling device quality assurance
  7. Neural Network Based Pitch Tracking In Very Noisy Speech
  8. Prosodic, spectral and voice quality feature selection using a long-term stopping criterion for audio-based emotion recognition
  9. Supervised non-negative matrix factorization for audio source separation
  10. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition
  11. Convolutional Data: Towards Deep Audio Learning from Big Data
  12. Physiologic Audio Fingerprinting

 

Auto-Encoder

  1. Dynamic Background Learning through Deep Auto-encoder Networks
  2. Topic-aware Deep Auto-encoders (tda) for Face Alignment
  3. An Adaptive Stacked Denoising Auto-Encoder Architecture for Human Action Recognition

 

Autoencoder

  1. DEEP LEARNING VIA STACKED SPARSE AUTOENCODERS FOR AUTOMATED VOXEL-WISE BRAIN PARCELLATION BASED ON FUNCTIONAL CONNECTIVITY (Thesis format: Monograph)
  2. Analyzing noise in autoencoders and deep networks
  3. Improving Transfer Learning Accuracy by Reusing Stacked Denoising Autoencoders
  4. Alternate Layer Sparsity and Intermediate Fine-tuning for Deep Autoencoders
  5. Effective Multi-Modal Retrieval based on Stacked Auto-Encoders
  6. Scheduled denoising autoencoders
  7. AN AUTOENCODER WITH BILINGUAL SPARSE FEATURES FOR IMPROVED STATISTICAL MACHINE TRANSLATION
  8. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  9. 3d object retrieval with stacked local convolutional autoencoder
  10. Chord Recognition with Stacked Denoising Autoencoders
  11. Deep Learning Representation using Autoencoder for 3d Shape Retrieval
  12. Autoencoder Trees
  13. Deep Directed Generative Autoencoders
  14. Feature Learning from Incomplete Eeg with Denoising Autoencoder
  15. The Potential Energy of an Autoencoder
  16. Auto-encoding Variational Bayes
  17. Recognition of Handwritten Characters in Chinese Legal Amounts by Stacked Autoencoders
  18. Improving generation performance of speech emotion recognition by denoising autoencoders
  19. Stacked Extreme Learning Machines
  20. Cross-modal Retrieval with Correspondence Autoencoder
  21. Relational Stacked Denoising Autoencoder for Tag Recommendation
  22. Learning Feature Representations with a Cost-Relevant Sparse Autoencoder
  23. Introduction to Autoencoders
  24. Multimodal Video Classification with Stacked Contractive Autoencoders
  25. Training Stacked Denoising Autoencoders for Representation Learning
  26. Made: Masked Autoencoder for Distribution Estimation
  27. Convergence of gradient based pre-training in Denoising autoencoders
  28. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  29. Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder
  30. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Autogression

  1. A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data

 

Autonomous

  1. Universal Memory Architectures for Autonomous Machines
  2. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Autonomously

  1. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Autoregression

  1. A Neural Autoregressive Approach to Attention-based Recognition

 

Back Propagation

  1. Back-Propagation Operation for Analog Neural Network Hardware with Synapse Components Having Hysteresis Characteristics
  2. Kickback cuts Backprop’s red-tape: Biologically plausible credit assignment in neural networks
  3. Momentum Effects on Back-Propagation Learning in a Multi-Layer Feed-Forward Neural Network

 

Bacteria

  1. Automatic Vaginal Bacteria Segmentation and Classification Based on Superpixel and Deep Learning

 

Barcode Detection

  1. Real-time Barcode Detection in the Wild

 

Batch

  1. Efficient batchwise dropout training using submatrices
  2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

 

Batch Normalization

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

 

Batchwise

  1. Efficient batchwise dropout training using submatrices

 

Bayes

  1. Agnostic Bayes

 

Bayesian

  1. A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis
  2. Bayesian Deep Deconvolutional Learning
  3. Interactions Between Gaussian Processes and Bayesian Estimation
  4. Towards Building Deep Networks with Bayesian Factor Graphs
  5. Scalable Bayesian Optimization Using Deep Neural Networks

 

Behavior Model

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Behavior Models

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Belief Propagation Networks

  1. Method and Apparatus for Spawning Specialist Belief Propagation Networks For Adjusting Exposure Settings

 

Bengio

  1. How transferable are features in deep neural networks?
  2. Handwritten Digits Classification
  3. Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding
  4. Show and Tell: A Neural Image Caption Generator
  5. Unsupervised Learning of Semantics of Object Detections for Scene Categorization
  6. End-to-end Continuous Speech Recognition using Attention-based Recurrent Nn: First Results
  7. Deep Learning
  8. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
  9. Supplementary Material: On the Number of Linear Regions of Deep Neural Networks
  10. Low precision arithmetic for deep learning
  11. Adasecant: Robust Adaptive Secant Method for Stochastic Gradient

 

Bifurcated Deep Network

  1. DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection

 

Big

  1. Random Bits Regression: a Strong General Predictor for Big Data
  2. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  3. Hypothesis Testing with Kernel Embeddings on Big and Interdependent Data
  4. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  5. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  6. Promises and Challenges of Big Data Computing in Health Sciences
  7. Deep learning applications and challenges in big data analytics
  8. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  9. Efficient Machine Learning for Big Data: A Review
  10. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Big Data

  1. Large-scale Deep Belief Nets with MapReduce
  2. Project Adam: Building an Efficient and Scalable Deep Learning Training System
  3. Traffic Flow Prediction With Big Data: A Deep Learning Approach
  4. Big Data Opportunities and Challenges: Discussions from Data Analytics Perspectives [Discussion Forum]
  5. Tensor index for large scale image retrieval
  6. Parallel deep neural network training for big data on blue gene/Q
  7. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  8. Practice in Synonym Extraction at Large Scale
  9. Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology
  10. Convolutional Data: Towards Deep Audio Learning from Big Data
  11. Random Bits Regression: a Strong General Predictor for Big Data
  12. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  13. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  14. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  15. Promises and Challenges of Big Data Computing in Health Sciences
  16. Deep learning applications and challenges in big data analytics
  17. Efficient Machine Learning for Big Data: A Review
  18. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Big-Data

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Bing Challenge

  1. Cross Modal Deep Model and Gaussian Process Based Model for MSR-Bing Challenge

 

Bioinformatics

  1. Deep learning of the tissue-regulated splicing code
  2. Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
  3. Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models
  4. Towards the Quantum Machine: Using Scalable Machine Learning Methods to Predict Photovoltaic Efficacy of Organic Molecules
  5. Multi-task Neural Networks for QSAR Predictions
  6. SSpro/ACCpro 5: Almost Perfect Prediction of Protein Secondary Structure and Relative Solvent Accessibility Using Profiles, Machine Learning, and Structural Similarity.
  7. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network
  8. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects
  9. A generative model of identifying informative proteins from dynamic Ppi networks
  10. Dann: a deep learning approach for annotating the pathogenicity of genetic variants
  11. Parallel deep neural network training for big data on blue gene/Q
  12. Automated computation of arbor densities: a step toward identifying neuronal cell types
  13. Improved contact predictions using the recognition of protein like contact patterns.
  14. Automated Gene Expression Pattern Annotation In The Mouse Brain
  15. Bimmer: a novel algorithm for detecting differential Dna methylation regions from MBDCap-seq data
  16. Possible computational filter to detect proteins associated to influenza A subtype H1n1.
  17. Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data
  18. Deep Belief Networks and Biomedical Text Categorisation
  19. lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning
  20. Comparative Study Of Machine Learning Techniques For Supervised Classification Of Biomedical Data
  21. An Innovative Svm for Wheat Seed Quality Estimation⋆

 

Biologically

  1. Towards Biologically Plausible Deep Learning

 

Biology

  1. Image-Based Analysis to Study Plant Infection with Human Pathogens
  2. What We Can Learn From the Primate’s Visual System

 

Bird

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity

 

Blstm

  1. Text recognition using deep Blstm networks

 

Boosted

  1. Image classification using boosted local features with random orientation and location selection

 

Boosting

  1. SelfieBoost: A Boosting Algorithm for Deep Learning

 

Bootstrapping

  1. Training Deep Neural Networks on Noisy Labels with Bootstrapping

 

Brain

  1. Deep learning based imaging data completion for improved brain disease diagnosis
  2. Feature Learning from Incomplete Eeg with Denoising Autoencoder
  3. Automated Gene Expression Pattern Annotation In The Mouse Brain
  4. Deep Extreme Learning Machine and Its Application in Eeg Classification
  5. Brain Ct Image Classification with Deep Neural Networks
  6. Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
  7. Hardware-Amenable Structural Learning for Spike-based Pattern Classification using a Simple Model of Active Dendrites
  8. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  9. Learning Deep Temporal Representations for Brain Decoding
  10. Brain Edge Detection
  11. Methodology and Techniques for Building Modular Brain-Computer Interfaces
  12. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation
  13. Pain: a distributed brain information network?
  14. A spectrum of sharing: maximization of information content for brain imaging data
  15. Brain as an Emergent Finite Automaton: A Theory and Three Theorems
  16. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  17. Neuraledugaming: A Mathematical “Brain” to Make Digital Edugames Smart
  18. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Brain Waves

  1. Does the beat go on?: identifying rhythms from brain waves recorded after their auditory presentation
  2. Classifying EEG recordings of rhythm perception
  3. Machines Learning-Towards a New Synthetic Autobiographical Memory
  4. Deep Learning for the Connectome

 

Caffe

  1. Bikers are like tobacco shops, formal dressers are like suits: Recognizing Urban Tribes with Caffe

 

Calibration

  1. Using Distance Estimation and Deep Learning to Simplify Calibration in Food Calorie Measurement

 

Cancer

  1. A proteomic signature predicts response to a therapeutic vaccine in pancreas cancer; analysis from the Gi-4000-02 trial
  2. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach
  3. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  4. Cancerous Cell Detection Using Histopathological Image Analysis
  5. Color Correction Arrangements For Dermoscopy
  6. Methods And Arrangements For Identifying Dermatological Diagnoses With Clinically Negligible Probabilties
  7. Automatic melanoma detection in dermatological images

 

Car Detection

  1. Joint Deep Learning for Car Detection

 

Cartography

  1. Large Materials Cartography: Representing and Mining Material Space Using Structural and Electronic Fingerprints

 

Cascade

  1. Cascade object detection with complementary features and algorithms

 

Cell

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Equity-Minded Learning Environments: Pla as a Portal to Fostering Inclusive Excellence

 

Challenges

  1. Big Data Deep Learning: Challenges and Perspectives
  2. Big Data Opportunities and Challenges: Discussions from Data Analytics Perspectives [Discussion Forum]
  3. Neural-Symbolic Learning and Reasoning: Contributions and Challenges
  4. The quality and reputation of open, distance and e-learning: what are the challenges?
  5. Promises and Challenges of Big Data Computing in Health Sciences
  6. Deep learning applications and challenges in big data analytics

 

Character Recognition

  1. A Study of Designing Compact Classifiers using Deep Neural Networks for Online Handwritten Chinese Character Recognition
  2. Recognition of Handwritten Characters in Chinese Legal Amounts by Stacked Autoencoders
  3. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  4. Robust Multi-Layer Hierarchical Model for Digit Character Recognition
  5. On the Performance Improvement of Devanagri Handwritten Character Recognition
  6. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

 

Chinese

  1. A Study of Deep Belief Network Based Chinese Speech Emotion Recognition

 

Classification

  1. DEFEATnet–A Deep Conventional Image Representation for Image Classification
  2. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  3. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  4. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  5. P300 classification using deep belief nets
  6. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  7. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  8. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  9. Constrained Extreme Learning Machines: A Study on Classification Cases
  10. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks
  11. Dynamic texture and scene classification by transferring deep image features
  12. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  13. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  14. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  15. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  16. Image Classification Using Generative Neuro Evolution for Deep Learning
  17. Imaging and representation learning of solar radio spectrums for classification
  18. Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification
  19. Deep learning for speech classification and speaker recognition
  20. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  21. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  22. Image classification using boosted local features with random orientation and location selection
  23. A novel pLSA based Traffic Signs Classification System
  24. Iterative 3d shape classification by online metric learning

 

Click-Through

  1. Deep Structured Semantic Model Produced Using Click-Through Data

 

Cloud

  1. A survey of research on cloud robotics and automation
  2. Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning
  3. Event Pattern Discovery on Ids Traces of Cloud Services
  4. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  5. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Clustered

  1. Deep Clustered Convolutional Kernels

 

Clustering

  1. Ghent University-iMinds at MediaEval 2014 Diverse Images: Adaptive Clustering with Deep Features
  2. Deep Embedding Network for Clustering
  3. A Convex Formulation for Spectral Shrunk Clustering
  4. Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering
  5. Improving relation descriptor extraction with word embeddings and cluster features
  6. SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering
  7. Soft context clustering for F0 modeling in HMM-based speech synthesis
  8. Deep Learning with Nonparametric Clustering
  9. Deep Learning with Nonparametric Clustering
  10. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  11. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  12. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  13. FaceNet: A Unified Embedding for Face Recognition and Clustering

 

Cnn

  1. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  2. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks

 

Coding Scheme

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization

 

Cognition

  1. Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment
  2. Deep Image: Scaling up Image Recognition
  3. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  4. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  5. Neural Implementation of Probabilistic Models of Cognition
  6. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  7. Sign language recognition using convolutional neural networks
  8. Robust face recognition via transfer learning for robot partner
  9. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  10. On the Performance Improvement of Devanagri Handwritten Character Recognition
  11. HFirst: A Temporal Approach to Object Recognition
  12. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  13. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  14. Hierarchical Recognition System for Target Recognition from Sparse Representations
  15. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  16. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  17. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  18. Scene Recognition by Manifold Regularized Deep Learning Architecture
  19. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  20. Noisy Training for Deep Neural Networks in Speech Recognition
  21. Learning invariant object recognition from temporal correlation in a hierarchical network
  22. Deep Multimodal Learning for Audio-Visual Speech Recognition
  23. DeepID3: Face Recognition with Very Deep Neural Networks
  24. Freehand Sketch Recognition Using Deep Features
  25. Deep Neural Networks for Sketch Recognition
  26. Face frontalization for Alignment and Recognition
  27. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  28. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  29. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  30. A Hmax with Llc for visual recognition
  31. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  32. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  33. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  34. Robust Excitation-based Features For Automatic Speech Recognition
  35. Learning Descriptors for Object Recognition and 3d Pose Estimation
  36. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  37. Machine Learning in Automatic Speech Recognition: A Survey
  38. DigiRec Proposal: Handwritten Digit Recognition in Hardware
  39. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  40. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  41. Text recognition using deep Blstm networks
  42. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  43. Face Recognition Based on Deep Learning
  44. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  45. Learning Compact Binary Face Descriptor for Face Recognition
  46. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  47. Facial Expression Recognition via Deep Learning
  48. Domain Adaptation for Visual Recognition
  49. Subset based deep learning for Rgb-d object recognition
  50. Deep learning for speech classification and speaker recognition
  51. FaceNet: A Unified Embedding for Face Recognition and Clustering
  52. Speech emotion recognition with unsupervised feature learning
  53. A Minimal Architecture for General Cognition
  54. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  55. Scene Text Detection and Recognition: Recent Advances and Future Trends

 

Cognitive

  1. Potential of Cognitive Computing and Cognitive Systems
  2. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  3. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Collaborative Filtering

  1. Implicitly Learning a User Interest Profile for Personalization of Web Search Using Collaborative Filtering
  2. A Distributional Representation Model For Collaborative Filtering

 

Combinatorical Optimization

  1. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization

 

Compression

  1. Stacked Quantizers for Compositional Vector Compression

 

Computer Vision

  1. Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines
  2. Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling
  3. Sparse Deep Belief Net Model for Visual Area {V2}
  4. An Overview of Color Name Applications in Computer Vision
  5. Deep learning of representations and its application to computer vision

 

Concept Learning

  1. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos

 

Consistency

  1. Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning

 

Constrained

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  2. Constrained Extreme Learning Machines: A Study on Classification Cases
  3. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators
  4. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Constructive Neural Networks

  1. Non-linear neighborhood component analysis based on constructive neural networks

 

Content-Based

  1. Utilizing Deep Learning for Content-based Community Detection

 

Contour Detection

  1. DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection

 

Controller

  1. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  2. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Convex

  1. A Convex Formulation for Spectral Shrunk Clustering

 

Convex Optimization

  1. Convolutional Neural Network and Convex Optimization

 

Convexity

  1. Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning

 

Convnet

  1. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition

 

Convnets

  1. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition

 

Convoluational Neural Network

  1. Context Dependent Encoding using Convolutional Dynamic Networks
  2. Permutohedral Lattice CNNs

 

Convolutional

  1. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  2. Sign language recognition using convolutional neural networks
  3. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  4. Robust Tracking via Convolutional Networks without Learning
  5. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  6. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  7. End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning
  8. A Data-Reuse Aware Accelerator for Large-Scale Convolutional Networks
  9. Pedestrian Detection Via Pca Filters Based Convolutional Channel
  10. Aircraft Detection by Deep Convolutional Neural Networks
  11. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  12. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  13. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  14. Detectionn guided deconvolutional network for hierarchical feature learning
  15. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  16. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  17. Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
  18. Convolutional Fusion Network for Face Verification in the Wild
  19. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  20. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  21. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  22. Deep Clustered Convolutional Kernels
  23. Deep Convolutional Inverse Graphics Network
  24. A theoretical argument for complex-valued convolutional networks
  25. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  26. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos
  27. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  28. Deep convolutional networks for pancreas segmentation in Ct imaging
  29. Conditional generative adversarial nets for convolutional face generation
  30. Rotation-invariant convolutional neural networks for galaxy morphology prediction
  31. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015

 

Convolutional Network

  1. A new 2.5 D representation for lymph node detection using random sets of deep convolutional neural network observations
  2. Learning a deep convolutional network for image super-resolution
  3. Improving multiview face detection with multi-task deep convolutional neural networks
  4. Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
  5. DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
  6. Evolving deep unsupervised convolutional networks for vision-based reinforcement learning
  7. Reducing structure of deep Convolutional Neural Networks for Huawei Accurate and Fast Mobile Video Annotation Challenge
  8. Distributed Asynchronous Optimization of Convolutional Neural Networks
  9. Handwritten Hangul recognition using deep convolutional neural networks
  10. Return of the Devil in the Details: Delving Deep into Convolutional Nets
  11. Learning Deep and Wide: A Spectral Method for Learning Deep Networks
  12. Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
  13. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
  14. Deep Epitomic Convolutional Neural Networks
  15. Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
  16. Large-scale video classification with convolutional neural networks
  17. Deep convolutional neural networks for sentiment analysis of short texts
  18. A Winner-Take-All Method for Training Sparse Convolutional Autoencoders
  19. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  20. Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning
  21. Using Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks for Partially Occluded Object Recognition
  22. CNN: Single-label to Multi-label
  23. Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics
  24. Action Recognition Using Ensemble of Deep Convolutional Neural Networks
  25. Discriminative Convolutional Sum-Product Networks on GPU
  26. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection
  27. A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval
  28. Towards Real-Time Image Understanding with Convolutional Networks
  29. One weird trick for parallelizing convolutional neural networks
  30. ImageNet Classification with Deep Convolutional Neural Networks
  31. Real-time continuous pose recovery of human hands using convolutional networks
  32. Vehicle License Plate Recognition With Random Convolutional Networks
  33. SimNets: A Generalization of Convolutional Networks
  34. Learning Sparse Feature Representations for Music Annotation and Retrievals
  35. Unsupervised Feature Learning for Audio Classification using Convolutional Deep Belief Networks
  36. Unsupervised learning of hierarchical representations with convolutional deep belief networks
  37. Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations
  38. Efficient Learning of Sparse, Distributed, Convolutional Feature Representations for Object Recognition
  39. Learning hierarchical representations for face verification with convolutional deep belief networks
  40. Look Closely: Learning Exemplar Patches for Recognizing Textiles from Product Images
  41. Cross Dataset Person Re-identification
  42. Recod at MediaEval 2014: Violent Scenes Detection Task
  43. Learning Convolutional NonLinear Features for K Nearest Neighbor Image Classification
  44. Early Hierarchical Contexts Learned by Convolutional Networks for Image Segmentation
  45. Deep Multimodal Fusion: Combining Discrete Events and Continuous Signals
  46. A new algorithm on variable-rate convolutional broadcast for network coding in cyclic networks
  47. A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks
  48. Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns
  49. Efficient Object Localization Using Convolutional Networks
  50. Long-term Recurrent Convolutional Networks for Visual Recognition and Description
  51. Fully Convolutional Networks for Semantic Segmentation
  52. Deep Deconvolutional Networks for Scene Parsing
  53. Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection
  54. Age Estimation by Multi-scale Convolutional Network
  55. Memory Bounded Deep Convolutional Networks
  56. Real-time object recognition and orientation estimation using an event-based camera and Cnn
  57. Occlusion Edge Detection in Rgb-d Frames using Deep Convolutional Networks
  58. Image Super-Resolution Using Deep Convolutional Networks
  59. Robust Tracking via Convolutional Networks without Learning
  60. A Data-Reuse Aware Accelerator for Large-Scale Convolutional Networks
  61. Detectionn guided deconvolutional network for hierarchical feature learning
  62. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  63. A theoretical argument for complex-valued convolutional networks
  64. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Convolutional Networks

  1. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
  2. A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis
  3. Persistent Evidence of Local Image Properties in Generic ConvNets
  4. Unsupervised feature learning on monaural Doa estimation using convolutional deep belief networks

 

Convolutional Neural Network

  1. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  2. Handwritten Hangul recognition using deep convolutional neural networks
  3. Modelling ‚Visualising and Summarising Documents with a Single Convolutional Neural Network
  4. Distributed Asynchronous Optimization of Convolutional Neural Networks
  5. An Efficient Implementation of Deep Convolutional Neural Networks on a Mobile Coprocessor
  6. Weighted Convolutional Neural Network Ensemble
  7. Deep convolutional neural networks for large-scale speech tasks
  8. Deformable Part Models are Convolutional Neural Networks
  9. Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks
  10. Going Deeper with Convolutions
  11. Tbcnn: A Tree-Based Convolutional Neural Network for Programming Language Processing
  12. 3d object retrieval with stacked local convolutional autoencoder
  13. A convolutional neural network approach for face verification
  14. Spatially-sparse convolutional neural networks
  15. Deep Convolutional Neural Networks With An Application Towards Geospatial Object Recognition
  16. Convolutional Neural Network and Convex Optimization
  17. Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors
  18. Raw Speech Signal-based Continuous Speech Recognition using Convolutional Neural Networks
  19. Music Genre Classification Using Convolutional Neural Network
  20. Vehicle Type Classification Using Unsupervised Convolutional Neural Network
  21. Cascaded Convolutional Neural Network for Eye Detection Under Complex Scenarios
  22. Vehicle Type Classification Using Semi-Supervised Convolutional Neural Network
  23. Deep Convolutional Neural Network for Image Deconvolution
  24. DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks
  25. Food Detection and Recognition Using Convolutional Neural Network
  26. Error-Driven Incremental Learning in Deep Convolutional Neural Network for Large-Scale Image Classification
  27. Fully Convolutional Neural Networks for Crowd Segmentation
  28. Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition
  29. Visual Sentiment Prediction with Deep Convolutional Neural Networks
  30. Learning to Generate Chairs with Convolutional Neural Networks
  31. The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
  32. Scene Recognition Using Mid-level features from Cnn
  33. Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
  34. Convolutional Neural Networks at Constrained Time Cost
  35. Image Recognition Using Convolutional Neural Networks
  36. Reading Text in the Wild with Convolutional Neural Networks
  37. Real-Time Grasp Detection Using Convolutional Neural Networks
  38. Teaching Deep Convolutional Neural Networks to Play Go
  39. Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification
  40. DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection
  41. Learning Block Group Sparse Representation Combined with Convolutional Neural Networks for Rgb-d Object Recognition
  42. Bayesian Deep Deconvolutional Learning
  43. Flattened Convolutional Neural Networks for Feedforward Acceleration
  44. Move Evaluation In Go Using Deep Convolutional Neural Networks
  45. Robotic Grasping System Using Convolutional Neural Networks
  46. Fully Convolutional Multi-Class Multiple Instance Learning
  47. Striving for Simplicity: The All Convolutional Net
  48. Learning Compact Convolutional Neural Networks with Nested Dropout
  49. Visual Scene Representations: Scaling and Occlusion in Convolutional Architectures
  50. Learning linearly separable features for speech recognition using convolutional neural networks
  51. Generative Modeling of Convolutional Neural Networks
  52. Spectral classification using convolutional neural networks
  53. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation
  54. Sign language recognition using convolutional neural networks
  55. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  56. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  57. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  58. Aircraft Detection by Deep Convolutional Neural Networks
  59. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  60. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  61. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  62. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  63. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  64. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  65. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  66. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos
  67. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  68. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Convolutional Neural Networks

  1. Memory Access Optimized Scheduling Scheme for DCNNs on a Mobile Processor
  2. Combining the Best of Graphical Models and ConvNets for Semantic Segmentation
  3. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

 

Corpora

  1. Applying deep learning techniques on medical corpora from the World Wide Web: a prototypical system and evaluation
  2. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  3. On Using Monolingual Corpora in Neural Machine Translation

 

Cortical Processing

  1. Correlated activity supports efficient cortical processing

 

Ct

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  3. Stochastic Spectral Descent for Restricted Boltzmann Machines
  4. Explicit knowledge extraction in information-theoretic supervised multi-layered Som
  5. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  6. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  7. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  8. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  9. On the Performance Improvement of Devanagri Handwritten Character Recognition
  10. HFirst: A Temporal Approach to Object Recognition
  11. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  12. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  13. Accurate localized short term weather prediction for renewables planning
  14. Utilizing Deep Learning for Content-based Community Detection
  15. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  16. Transductive Multi-view Zero-Shot Learning
  17. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  18. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  19. Video summarization based on Subclass Support Vector Data Description
  20. Retrieval Term Prediction Using Deep Belief Networks
  21. Scene Recognition by Manifold Regularized Deep Learning Architecture
  22. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  23. Neural Networks Based Methods for Voice Activity Detection in a Multi-room Domestic Environment
  24. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  25. An Effective Solution to Double Counting Problem in Human Pose Estimation
  26. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  27. Where am I? Predicting Montreal Neighbourhoods from Google Street View Images
  28. Learning invariant object recognition from temporal correlation in a hierarchical network
  29. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  30. Filtered Channel Features for Pedestrian Detection
  31. Deep Twin Support Vector Machine
  32. Pedestrian Detection Via Pca Filters Based Convolutional Channel
  33. A spectrum of sharing: maximization of information content for brain imaging data
  34. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  35. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  36. Interactions Between Gaussian Processes and Bayesian Estimation
  37. Aircraft Detection by Deep Convolutional Neural Networks
  38. Exploring Latent Structure in Data: Algorithms and Implementations
  39. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  40. Advanced Mean Field Theory of Restricted Boltzmann Machine
  41. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  42. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  43. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  44. Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
  45. Exploration of Deep Belief Networks for Vowel-like regions detection
  46. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  47. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  48. Continuous Hyper-parameter Learning for Support Vector Machines
  49. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  50. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  51. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  52. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  53. Adaptive Road Detection via Context-aware Label Transfer
  54. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  55. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  56. Detectionn guided deconvolutional network for hierarchical feature learning
  57. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  58. Fast Neural Networks with Circulant Projections
  59. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  60. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  61. ‘Hiring a Nashville sensation': using narrative learning to develop the problem solving skills of contract law students
  62. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  63. Inferring 3d Object Pose in Rgb-d Images
  64. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  65. Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships
  66. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  67. Towards Building Deep Networks with Bayesian Factor Graphs
  68. Abstract Learning via Demodulation in a Deep Neural Network
  69. Deep Transform: Error Correction via Probabilistic Re-Synthesis
  70. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  71. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  72. Principles of Explanatory Debugging to Personalize Interactive Machine Learning
  73. Universal Memory Architectures for Autonomous Machines
  74. Rectified Factor Networks
  75. Artificial intelligence: Learning to see and act
  76. Learning Descriptors for Object Recognition and 3d Pose Estimation
  77. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  78. Detecting spammers on social Networks
  79. Forecasting And Inventory Performance In Direct-store Delivery Supply Chain: Case Of Retailer In Serbia
  80. A Dictionary Approach to Ebsd Indexing
  81. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  82. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  83. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  84. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  85. Learning Semantic Hierarchies: A Continuous Vector Space Approach
  86. When Are Tree Structures Necessary for Deep Learning of Representations?
  87. Cascade object detection with complementary features and algorithms
  88. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  89. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  90. Two-Stage Learning to Predict Human Eye Fixations via SDAEs
  91. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  92. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis
  93. Predicting the Quality of User-Generated Answers Using Co-Training in Community-based Question Answering Portals
  94. Imaging and representation learning of solar radio spectrums for classification
  95. Robust people counting using sparse representation and random projection
  96. Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer
  97. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  98. Unsupervised word sense induction using rival penalized competitive learning
  99. Deep Human Parsing with Active Template Regression
  100. Learning Compact Binary Face Descriptor for Face Recognition
  101. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  102. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation
  103. Deep Reinforcement Learning for constructing meaning by ‘babbling’
  104. Subset based deep learning for Rgb-d object recognition
  105. Awareness, Integration and Interconnectedness Contemplative Practices of Higher Education Professionals
  106. Mask selective regularization for restricted Boltzmann machines
  107. Deep Structured Semantic Model Produced Using Click-Through Data
  108. Knowledge Representation for Image Feature Extraction
  109. Single image super-resolution by approximated Heaviside functions
  110. Automatic melanoma detection in dermatological images
  111. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”
  112. Predicting Entry-Level Categories
  113. Predicting Pinterest: Automating a distributed human computation
  114. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images
  115. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  116. A Minimal Architecture for General Cognition
  117. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  118. Feature maps driven no-reference image quality prediction of authentically distorted images
  119. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  120. Image classification using boosted local features with random orientation and location selection
  121. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  122. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  123. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  124. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  125. Scene Text Detection and Recognition: Recent Advances and Future Trends
  126. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  127. Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning
  128. Deep convolutional networks for pancreas segmentation in Ct imaging
  129. Deep Transform: Time-Domain Audio Error Correction via Probabilistic Re-Synthesis
  130. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview
  131. Learning Hypergraph-regularized Attribute Predictors
  132. Predicting ocean health, one plankton at a time
  133. Optimizing Neural Networks with Kronecker-factored Approximate Curvature
  134. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis
  135. Detection of Alzheimer’s disease using group lasso SVM-based region selection
  136. Vehicle Detection in Aerial Imagery: A small target detection benchmark
  137. Rotation-invariant convolutional neural networks for galaxy morphology prediction
  138. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015
  139. On Invariance and Selectivity in Representation Learning
  140. Rank Subspace Learning for Compact Hash Codes
  141. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder
  142. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Data Center

  1. Can Congestion in Data Center Networks Be Predicted By Of Time Of Day?

 

Data Mining

  1. Ai for Data Mining

 

Data-Parallel

  1. Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning

 

Dataset

  1. Large-Scale Deep Learning on the Yfcc100m Dataset
  2. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis

 

Dcnn

  1. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation

 

Decision Making

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Decision Tree

  1. Clinical Decision Analysis using Decision Tree

 

Deep Belief Nets

  1. P300 classification using deep belief nets

 

Deep Belief Network

  1. Towards adaptive learning with improved convergence of deep belief networks on graphics processing units
  2. Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection
  3. Using Deep Belief Networks for Vector-Based Speaker Recognition
  4. Statistical Parametric Speech Synthesis using Weighted Multi-distribution Deep Belief Network
  5. Deep Belief Networks (DBNs)
  6. Using Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks for Partially Occluded Object Recognition
  7. Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning
  8. Large-scale Deep Belief Nets with MapReduce
  9. Camera-based Sudoku recognition with Deep Belief Network
  10. Prediction of Stock Trend Based on Deep Belief Networks
  11. Deep Tempering
  12. Accuracy evaluation of deep belief networks with fixed-point arithmetic
  13. Deep Adaptive Networks for Visual Data Classification
  14. Learning Local Receptive Fields in Deep Belief Networks for Visual Feature Detection
  15. Deep learning-based target customer position extraction on social network
  16. Deep belief network based Crf for spoken language understanding
  17. A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks
  18. Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images
  19. Deep Belief Network Training Improvement Using Elite Samples Minimizing Free Energy
  20. Systems and methods for analyzing data using deep belief networks (dbn) and identifying a pattern in a graph
  21. Deep Belief Networks and Biomedical Text Categorisation
  22. Unsupervised feature learning on monaural Doa estimation using convolutional deep belief networks
  23. A Study of Deep Belief Network Based Chinese Speech Emotion Recognition
  24. Auditory Scene Classification with Deep Belief Network
  25. Retrieval Term Prediction Using Deep Belief Networks
  26. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  27. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  28. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks
  29. Exploration of Deep Belief Networks for Vowel-like regions detection
  30. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network
  31. Speech Separation based on Deep Belief Network
  32. Learning Document Semantic Representation with Hybrid Deep Belief Network

 

Deep Boltzmann Machines

  1. Learning High-level Features by Deep Boltzmann Machines for Handwriting Digits Recogintion

 

Deep Convex Networks

  1. Kernel Deep Convex Networks And End-to-end Learning

 

Deep Learning

  1. From multiple views to single view: a neural network approach

 

Deep Neural Network

  1. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network
  2. Recognition Of Acoustic Events Using Deep Neural Networks
  3. Audio Concept Classification With Hierarchical Deep Neural Networks
  4. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training
  5. Classification of Artistic Styles using Binarized Features Derived from a Deep Neural Network
  6. Deep neural network based load forecast
  7. Parallel batch pattern training algorithm for deep neural network
  8. Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network
  9. Qr Code Localization Using Deep Neural Networks
  10. Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition
  11. A Real-time Hand Posture Recognition System Using Deep Neural Networks
  12. A Deep Neural Network Approach to Automatic Birdsong Recognition
  13. Binaural Classification for Reverberant Speech Segregation Using Deep Neural Networks
  14. Deep Neural Networks For Spoken Dialog Systems
  15. Parallel deep neural network training for big data on blue gene/Q
  16. A Study of Designing Compact Classifiers using Deep Neural Networks for Online Handwritten Chinese Character Recognition
  17. Acoustic emotion recognition using deep neural network
  18. Research on deep neural network’s hidden layers in phoneme recognition
  19. Cross-language transfer learning for deep neural network based speech enhancement
  20. Improving training time of deep neural networkwith asynchronous averaged stochastic gradient descent
  21. Multiple time-span feature fusion for deep neural network modeling
  22. Investigation of stochastic Hessian-Free optimization in Deep neural networks for speech recognition
  23. TANDEM-bottleneck feature combination using hierarchical Deep Neural Networks
  24. Random feedback weights support learning in deep neural networks
  25. How transferable are features in deep neural networks?
  26. Deep Neural Network Based Speech Separation for Robust Speech Recognition
  27. An Optimization of Deep Neural Networks in Asr using Singular Value Decomposition
  28. Speech Separation of A Target Speaker Based on Deep Neural Networks
  29. Real-time Head Orientation from a Monocular Camera using Deep Neural Network
  30. Deep Neural Networks
  31. Brain Ct Image Classification with Deep Neural Networks
  32. Feature Representation Learning in Deep Neural Networks
  33. Representation Sharing and Transfer in Deep Neural Networks
  34. Deep Neural Network-Hidden Markov Model Hybrid Systems
  35. Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features
  36. A Survey of Regularization Methods for Deep Neural Network
  37. Environmentally robust Asr front-end for deep neural network acoustic models
  38. Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
  39. Object Recognition Using Deep Neural Networks: A Survey
  40. Supplementary Material: On the Number of Linear Regions of Deep Neural Networks
  41. No-reference image quality assessment with shearlet transform and deep neural Networks
  42. Deep neural network adaptation for children’s and adults’ speech recognition
  43. Towards Deep Neural Network Architectures Robust to Adversarial Examples
  44. Fixed-point feedforward deep neural network design using weights+ 1, 0, and− 1
  45. Learning Activation Functions to Improve Deep Neural Networks
  46. Training Deep Neural Networks on Noisy Labels with Bootstrapping
  47. Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks
  48. An analysis of deep neural networks for texture classification
  49. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers
  50. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  51. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  52. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks
  53. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  54. Keystroke Dynamics Advances for Mobile Devices Using Deep Neural Network
  55. Noisy Training for Deep Neural Networks in Speech Recognition
  56. DeepID3: Face Recognition with Very Deep Neural Networks
  57. Deep Neural Networks for Sketch Recognition
  58. Over-Sampling in a Deep Neural Network
  59. Abstract Learning via Demodulation in a Deep Neural Network
  60. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  61. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  62. Scalable Bayesian Optimization Using Deep Neural Networks
  63. Sequence transcription with deep neural networks
  64. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  65. Improving acoustic model for English Asr System using deep neural network
  66. Deep Neural Networks for Acoustic Modeling
  67. Data driven articulatory synthesis with deep neural networks

 

Deep Sigmoid Belief Networks

  1. Learning Deep Sigmoid Belief Networks with Data Augmentation

 

Deeply-Supervised Nets

  1. Deeply-Supervised Nets

 

Deformation

  1. Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection

 

Deformations

  1. Deep Adaptive Log-Demons–Diffeomorphic Image Registration with Very Large Deformations

 

Demodulation

  1. Abstract Learning via Demodulation in a Deep Neural Network

 

Denoising

  1. Training Stacked Denoising Autoencoders for Representation Learning
  2. Convergence of gradient based pre-training in Denoising autoencoders
  3. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  4. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Depression

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression

 

Depth Estimation

  1. Deep Convolutional Neural Fields for Depth Estimation from a Single Image

 

Depth-Videos

  1. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos

 

Dermatology

  1. Gesture-based Dermatologic Data Collection And Presentation

 

Devops

  1. Can Congestion in Data Center Networks Be Predicted By Of Time Of Day?

 

Diabetes

  1. Predicting Likelihood of Hospitalization with Subset-Filtered Emerging Patterns

 

Diabetic

  1. Diagnosis Of Diabetic Retinopathy By Segmentation Of Blood Vessels In Retinal Images

 

Diacritization

  1. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization

 

Dictionary

  1. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  2. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  3. A Dictionary Approach to Ebsd Indexing

 

Dictionary Extraction

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity

 

Digit Classification

  1. Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights

 

Digit Recognition

  1. Robust continuous digit recognition using reservoir computing

 

Disambiguation

  1. Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning

 

Discriminative

  1. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  2. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  3. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  4. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  5. Learning Discriminative Feature Representations for Visual Categorization

 

Discriminative Learning

  1. Matrix and Tensor Features for Discriminative Learning

 

Disease

  1. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  2. Pd Disease State Assessment in Naturalistic Environments using Deep Learning
  3. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Disjunctive

  1. Disjunctive Normal Networks

 

Distance Functions

  1. A Probabilistic Multiple Criteria Sorting Approach Based On Distance Functions

 

Distributed

  1. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  2. Singa: A Distributed System for Deep Learning
  3. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation
  4. Predicting Pinterest: Automating a distributed human computation
  5. Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

 

Distributed System

  1. Distributed Training of Neural Network Language Models

 

Dnn

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments

 

Domain Invariance

  1. Deep Domain Confusion: Maximizing for Domain Invariance

 

Domain-Adversarial

  1. Domain-Adversarial Neural Networks

 

Drone

  1. Modular deep Recurrent Neural Network: Application to quadrotors

 

Dropout

  1. Temporal Dropout of Changes Approach to Convolutional Learning of Spatio-Temporal Features
  2. On the Inductive Bias of Dropout
  3. Learning Compact Convolutional Neural Networks with Nested Dropout
  4. Efficient batchwise dropout training using submatrices

 

Drug

  1. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features

 

Drug Target Detection

  1. Multi-Task Deep Networks for Drug Target Prediction

 

Economy

  1. Pre-release sales forecasting: A model-driven context feature extraction approach

 

Edge Detection

  1. Occlusion Edge Detection in Rgb-d Frames using Deep Convolutional Networks

 

Education

  1. Contexto: lessons learned from mobile context inference
  2. Predicting Academic Achievement of High-School Students Using Machine Learning

 

Eeg

  1. Classifying EEG recordings of rhythm perception
  2. Feature Learning from Incomplete Eeg with Denoising Autoencoder
  3. Deep Extreme Learning Machine and Its Application in Eeg Classification
  4. Learning Deep Temporal Representations for Brain Decoding
  5. Methodology and Techniques for Building Modular Brain-Computer Interfaces

 

Electricity

  1. Wind Power Prediction and Pattern Feature Based on Deep Learning Method

 

Electricity Forecast

  1. Deep neural network based load forecast

 

Embedded

  1. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators

 

Emotion

  1. Deep Learning for Emotional Speech Recognition
  2. Prosodic, spectral and voice quality feature selection using a long-term stopping criterion for audio-based emotion recognition
  3. Acoustic emotion recognition using deep neural network
  4. Improving generation performance of speech emotion recognition by denoising autoencoders
  5. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video
  6. Speech Emotion Recognition Using Cnn
  7. Emotion Modeling and Machine Learning in Affective Computing
  8. Emotion Recognition in the Wild with Feature Fusion and Multiple Kernel Learning
  9. A Study of Deep Belief Network Based Chinese Speech Emotion Recognition
  10. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  11. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  12. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  13. Speech emotion recognition with unsupervised feature learning

 

Emotion Detection

  1. Emotion Detection using Deep Belief Networks
  2. Spoken emotion recognition using deep learning

 

Encoding

  1. Two-layer contractive encodings for learning stable nonlinear features
  2. Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction

 

Encryption

  1. Crypto-nets: Neural Networks Over En-crypted Data

 

Energy

  1. Quantum Energy Regression using Scattering Transforms
  2. Efficient Generation of Energy and Performance Pareto Front for Fpga Designs
  3. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters
  4. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Energy Efficiency

  1. Quantifying the Energy Efficiency of Object Recognition and Optical Flow

 

Energy Efficient

  1. M2C: Energy efficient mobile cloud system for deep learning
  2. Energy efficient neural networks for big data analytics
  3. Brain-inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform
  4. Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition
  5. Stt-snn: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks

 

Ensemble Learning

  1. Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning
  2. Soft sensor development for nonlinear and time‐varying processes based on supervised ensemble learning with improved process state partition

 

Entities

  1. Entity-centric search: querying by entities and for entities

 

Entity

  1. Entity-centric search: querying by entities and for entities

 

Error Correction

  1. Deep Transform: Error Correction via Probabilistic Re-Synthesis
  2. Deep Transform: Time-Domain Audio Error Correction via Probabilistic Re-Synthesis

 

Estimation

  1. Nice: Non-linear Independent Components Estimation
  2. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  3. An Effective Solution to Double Counting Problem in Human Pose Estimation
  4. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  5. Interactions Between Gaussian Processes and Bayesian Estimation
  6. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  7. Hands Deep in Deep Learning for Hand Pose Estimation
  8. Using Distance Estimation and Deep Learning to Simplify Calibration in Food Calorie Measurement
  9. Made: Masked Autoencoder for Distribution Estimation
  10. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  11. Learning Descriptors for Object Recognition and 3d Pose Estimation
  12. Deeply-Learned Feature for Age Estimation
  13. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  14. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Evaluation

  1. Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns
  2. CIDEr: Consensus-based Image Description Evaluation
  3. Preliminary evaluation of hyperopt algorithms on HPOLib
  4. Software Quality Evaluation of Face Recognition APIs & Libraries

 

Event

  1. Event Pattern Discovery on Ids Traces of Cloud Services
  2. Spike Event Based Learning in Neural Networks

 

Event Detection

  1. Video Event Detection via Multi-modality Deep Learning
  2. Audio-Concept Features and Hidden Markov Models for Multimedia Event Detection

 

Examination

  1. A critical examination of deep learning approaches to automated speech recognition

 

Experimental

  1. Shallow Classification or Deep Learning: An Experimental Study

 

Extreme Learning

  1. A Deep and Stable Extreme Learning Approach for Classification and Regression⋆

 

Eye Detection

  1. Eye gaze for spoken language understanding in multi-modal conversational interactions
  2. Smartphone based visible iris recognition using deep sparse filtering
  3. Cascaded Convolutional Neural Network for Eye Detection Under Complex Scenarios

 

Eye Tracking

  1. Eye Localization Based on Multi-Channel Correlation Filter Bank

 

Face

  1. Robust face recognition via transfer learning for robot partner
  2. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  3. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  4. DeepID3: Face Recognition with Very Deep Neural Networks
  5. Face frontalization for Alignment and Recognition
  6. Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
  7. Dense 3d Face Alignment from 2d Videos in Real-Time
  8. Convolutional Fusion Network for Face Verification in the Wild
  9. Supervised descent method with low rank and sparsity constraints for robust face alignment
  10. Face Recognition Based on Deep Learning
  11. Learning Compact Binary Face Descriptor for Face Recognition
  12. FaceNet: A Unified Embedding for Face Recognition and Clustering
  13. Logistic Similarity Metric Learning For Face Verification
  14. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview
  15. Conditional generative adversarial nets for convolutional face generation

 

Face Detection

  1. Improving multiview face detection with multi-task deep convolutional neural networks
  2. Learning to encode motion using spatio-temporal synchrony
  3. Detecting People in Cubist Art
  4. Deep Metric Learning for Person Re-Identification
  5. Cross Dataset Person Re-identification

 

Face Expression Analysis

  1. Facial Expression Analysis Based on High Dimensional Binary Features

 

Face Recognition

  1. Deep learning for real-time robust facial expression recognition on a smartphone
  2. Deep learning multi-view representation for face recognition
  3. Deep learning face representation by joint identification-verification
  4. Learning and Transferring Multi-task Deep Representation for Face Alignment
  5. Facial Landmark Detection by Deep Multi-task Learning
  6. Shared Representation Learning for Heterogeneous Face Recognition
  7. Web-Scale Training for Face Identification
  8. Emotion Detection using Deep Belief Networks
  9. Hough Networks for Head Pose Estimation and Facial Feature Localization
  10. Human Action Recognition Using Deep Probabilistic Graphical Models
  11. Recurrent Models of Visual Attention
  12. Deep learning: Modeling high-level face features through deep networks
  13. Recognition of Facial Attributes using Adaptive Sparse Representations of Random Patches
  14. Hough Networks for Head Pose Estimation and Facial Feature Localization
  15. A Neural Autoregressive Approach to Attention-based Recognition
  16. Recognition of Facial Expression via Kernel Pca Network
  17. Deep Regression for Face Alignment
  18. A convolutional neural network approach for face verification
  19. Facial Landmark Localization using Hierarchical Pose Regression
  20. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  21. A Deep Graph Embedding Network Model for Face Recognition
  22. Learning Multiscale Active Facial Patches for Expression Analysis
  23. Fast Localization of Facial Landmark Points
  24. The relation of eye gaze and face pose: Potential impact on speech recognition
  25. Low rank driven robust facial landmark regression
  26. Deep Representations for Iris, Face, and Fingerprint Spoofing Attack Detection
  27. Facial Feature Point Detection: A Comprehensive Survey
  28. Learning Invariant Color Features for Person Re-Identification
  29. Extended Supervised Descent Method for Robust Face Alignment
  30. Facial Expression Analysis Based on High Dimensional Binary Features
  31. DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification
  32. Discriminative Deep Face Shape Model for Facial Point Detection
  33. Learning Compact Face Representation: Packing a Face into an int32
  34. Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations
  35. Set-label modeling and deep metric learning on person re-identification
  36. Automatic face annotation in Tv series by video/script alignment
  37. Real-time Head Orientation from a Monocular Camera using Deep Neural Network
  38. Topic-aware Deep Auto-encoders (tda) for Face Alignment
  39. Deep Learning Face Attributes in the Wild
  40. Effective Face Frontalization in Unconstrained Images
  41. Learning Face Representation from Scratch
  42. Deeply learned face representations are sparse, selective, and robust
  43. Shared features for multiple face-based biometrics
  44. A twice face recognition algorithm
  45. Feature Selection And Extraction For Babyface Recognition
  46. Personalized Face Image Retrieval Based On Gmkl
  47. Software Quality Evaluation of Face Recognition APIs & Libraries
  48. Online Smart Face Morphing Engine with Prior Constraints and Local Geometry Preservation
  49. A Learning Framework for Age Rank Estimation based on Face Images with Scattering Transform
  50. Privileged Information-based Conditional Structured Output Regression Forest for Facial Point Detection
  51. Robust face recognition via transfer learning for robot partner
  52. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  53. DeepID3: Face Recognition with Very Deep Neural Networks
  54. Face Recognition Based on Deep Learning
  55. Learning Compact Binary Face Descriptor for Face Recognition
  56. FaceNet: A Unified Embedding for Face Recognition and Clustering

 

Facial

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  2. Learning facial expressions from an image
  3. Facial Expression Recognition via Deep Learning
  4. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Factorization

  1. SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering
  2. Neural Network Regularization via Robust Weight Factorization

 

Fault Diagnosis

  1. Deep learning for fault diagnosis based on multi-sourced heterogeneous data

 

Feature

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  3. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  4. Learning features and their transformations from natural videos
  5. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  6. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  7. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  8. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  9. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  10. Filtered Channel Features for Pedestrian Detection
  11. Freehand Sketch Recognition Using Deep Features
  12. Dynamic texture and scene classification by transferring deep image features
  13. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  14. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  15. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  16. Detectionn guided deconvolutional network for hierarchical feature learning
  17. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  18. Dynamic Feature-Adaptive Subdivision
  19. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  20. Robust Excitation-based Features For Automatic Speech Recognition
  21. Deeply-Learned Feature for Age Estimation
  22. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  23. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  24. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  25. Cascade object detection with complementary features and algorithms
  26. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  27. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  28. On the Problem of Features Variability in Sequence Learning Problems
  29. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  30. Fitting 3d Morphable Models using Local Features
  31. Knowledge Representation for Image Feature Extraction
  32. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images
  33. Speech emotion recognition with unsupervised feature learning
  34. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  35. Learning Discriminative Feature Representations for Visual Categorization
  36. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  37. Feature maps driven no-reference image quality prediction of authentically distorted images
  38. Image classification using boosted local features with random orientation and location selection
  39. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015

 

Feature Discovery

  1. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images

 

Feature Encoding

  1. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos

 

Feature Extraction

  1. Hierarchical spatiotemporal feature extraction using recurrent online clustering
  2. Caffe: Convolutional Architecture for Fast Feature Embedding
  3. Deep learning of feature representation with multiple instance learning for medical image analysis
  4. A review of unsupervised feature learning and deep learning for time-series modeling
  5. Challenge Huawei challenge: Fusing multimodal features with deep neural networks for Mobile Video Annotation
  6. Analysis of Feature Maps Selection in Supervised Learning Using Convolutional Neural Networks
  7. Learning Rich Features from RGB-D Images for Object Detection and Segmentation
  8. Improved Music Feature Learning with Deep Neural Networks
  9. Feature Selection and Learning for Semantic Segmentation
  10. Audio-only bird classification using unsupervised feature learning
  11. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  12. Feature Selection Based on Dependency Margin
  13. Improving Acoustic Model for Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Bottleneck Features
  14. Local deep feature learning framework for 3d shape
  15. Learning Sparse Feature Representations for Music Annotation and Retrievals
  16. Unsupervised Feature Learning for Audio Classification using Convolutional Deep Belief Networks
  17. Efficient Learning of Sparse, Distributed, Convolutional Feature Representations for Object Recognition
  18. Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines
  19. Learning and Selecting Features Jointly with Point-wise Gated {Boltzmann} Machines
  20. An exact mapping between the Variational Renormalization Group and Deep Learning
  21. Meta-parameter free unsupervised sparse feature learning
  22. High-Order Semi-RBMs and Deep Gated Neural Networks for Feature Interaction Identification and Non-Linear Semantic Indexing
  23. Unsupervised Feature Learning For Bootleg Detection Using Deep Learning Architectures
  24. Learning Local Receptive Fields in Deep Belief Networks for Visual Feature Detection
  25. Recod at MediaEval 2014: Violent Scenes Detection Task
  26. A Method For Extracting Information From The Web Using Deep Learning Algorithm
  27. Feature Mapping of Multiple Beamformed Sources for Robust Overlapping Speech Recognition Using a Microphone Array
  28. Learning Multiple Complex Features Based on Classification Results
  29. Multiple time-span feature fusion for deep neural network modeling
  30. Pre-release sales forecasting: A model-driven context feature extraction approach
  31. Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection
  32. Da-ccd: A novel action representation by deep architecture of local depth feature
  33. Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering
  34. Wind Power Prediction and Pattern Feature Based on Deep Learning Method
  35. Geodesic Invariant Feature (gif): A Local Descriptor in Depth
  36. Prototype-Based Discriminative Feature Learning for Kinship Verification
  37. Visual Causal Feature Learning
  38. Matrix and Tensor Features for Discriminative Learning
  39. Integrating Stroke-distribution Information Into Spatial Feature Extraction For Automatic Handwriting Recognition
  40. Feature Weight Tuning for Recursive Neural Networks
  41. Score Function Features for Discriminative Learning: Matrix and Tensor Framework
  42. Sparse, guided feature connections in an Abstract Deep Network
  43. Exploiting high level feature for dynamic textures recognition
  44. Learning Feature Representations with a Cost-Relevant Sparse Autoencoder
  45. Feature Selection And Extraction For Babyface Recognition
  46. Learning linearly separable features for speech recognition using convolutional neural networks
  47. C-SVDDNet: An Effective Single-Layer Network for Unsupervised Feature Learning
  48. View-independent object detection using shared local features
  49. lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning
  50. Unsupervised Feature Learning for Dense Correspondences across Scenes
  51. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  52. Knowledge Representation for Image Feature Extraction

 

Feature Recognition

  1. Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features

 

Feature Representation

  1. Feature Representation Learning in Deep Neural Networks
  2. Sharing Model With Multi-level Feature Representations

 

Feature Selection

  1. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters

 

Feature Tuning

  1. Feature Weight Tuning for Recursive Neural Networks

 

Features

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Learning features and their transformations from natural videos
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Filtered Channel Features for Pedestrian Detection
  5. Freehand Sketch Recognition Using Deep Features
  6. Dynamic texture and scene classification by transferring deep image features
  7. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  8. Robust Excitation-based Features For Automatic Speech Recognition
  9. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  10. Cascade object detection with complementary features and algorithms
  11. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  12. On the Problem of Features Variability in Sequence Learning Problems
  13. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  14. Fitting 3d Morphable Models using Local Features
  15. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  16. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  17. Image classification using boosted local features with random orientation and location selection

 

Filtering

  1. Depth of field rendering via adaptive recursive filtering

 

Finance

  1. Neural Networks for Runtime Verification
  2. Gpu Implementation of a Deep Learning Network for Financial Prediction

 

Fine Tuning

  1. Statistical-mechanical analysis of pre-training and fine tuning in deep learning

 

Fine-Tuning

  1. DeepHash: Getting Regularization, Depth and Fine-Tuning Right

 

Fingerprint Detection

  1. Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns

 

Fingerprint Recognition

  1. Fingerprint Classification Based on Depth Neural Network
  2. Deep Representations for Iris, Face, and Fingerprint Spoofing Attack Detection

 

Fisher Vectors

  1. Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation

 

Fmri

  1. Deep learning of fMRI big data: a novel approach to subject-transfer decoding

 

Font Recognition

  1. Decomposition-Based Domain Adaptation for Real-World Font Recognition

 

Food Detection

  1. Food Detection and Recognition Using Convolutional Neural Network

 

Fpga

  1. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  2. Efficient Generation of Energy and Performance Pareto Front for Fpga Designs

 

Fpga-Based

  1. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks

 

Framework

  1. Purine: A bi-graph based deep learning framework
  2. A Learning Framework for Age Rank Estimation based on Face Images with Scattering Transform
  3. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  4. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework
  5. Emeuro: a framework for generating multi-purpose accelerators via deep learning
  6. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  7. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  8. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  9. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Freehand

  1. Freehand Sketch Recognition Using Deep Features

 

Frequency Domain

  1. Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images

 

Fuzzy Learning

  1. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery

 

Galaxy

  1. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Game

  1. Deep learning for real-time Atari game play using offline Monte-Carlo tree search planning

 

Games

  1. Replicating the Paper “Playing Atari with Deep Reinforcement Learning”[MKS
  2. Camera-based Sudoku recognition with Deep Belief Network
  3. Learning with serious games: is fun playing the game a predictor of learning success?
  4. Teaching Deep Convolutional Neural Networks to Play Go
  5. Move Evaluation In Go Using Deep Convolutional Neural Networks
  6. Neuraledugaming: A Mathematical “Brain” to Make Digital Edugames Smart

 

Gaussian

  1. Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features
  2. Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation
  3. Interactions Between Gaussian Processes and Bayesian Estimation

 

Generative

  1. Generative Adversarial Nets
  2. Image Classification Using Generative Neuro Evolution for Deep Learning
  3. GSNs: Generative Stochastic Networks
  4. Conditional generative adversarial nets for convolutional face generation

 

Generative Deep Learning

  1. Implementation of discriminative and generative deep learning

 

Genetic Programming

  1. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach

 

Gesture

  1. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Gesture Recognition

  1. Deep Dynamic Neural Networks for Gesture Segmentation and Recognition
  2. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  3. A Study of Feature Combination in Gesture Recognition with Kinect
  4. Feature learning based on Sae-pca network for Human gesture recognition in Rgbd images
  5. A hierarchical structure for gesture recognition using Rgb-d sensor
  6. ModDrop: adaptive multi-modal gesture recognition

 

Go

  1. Teaching Deep Convolutional Neural Networks to Play Go
  2. Move Evaluation In Go Using Deep Convolutional Neural Networks

 

Googlenet

  1. A Gpu Implementation of GoogLeNet

 

Gpu

  1. A fast deep learning system using GPU
  2. GPU Accelerated Computation and Real-time Rendering of Cellular Automata Model for Spatial Simulation
  3. Towards adaptive learning with improved convergence of deep belief networks on graphics processing units
  4. GPUs: High-performance Accelerators for Parallel Applications: The multicore transformation (Ubiquity symposium)
  5. Large scale recurrent neural network on GPU
  6. Detection of retransmissions in 10G Ethernet using GPUs
  7. More Faster Self-Organizing Maps by General Purpose on Graphics Processing Units
  8. Fast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks
  9. Discriminative Convolutional Sum-Product Networks on GPU
  10. Determining the difficulty of accelerating problems on a Gpu
  11. Optimising Purely Functional Gpu Programs (Thesis)
  12. Gpu Implementation of a Deep Learning Network for Financial Prediction
  13. cuDNN: Efficient Primitives for Deep Learning
  14. Introducing CURRENNT–the Munich open-source Cuda RecurREnt Neural Network Toolkit
  15. Gaussian Process Models with Parallelization and Gpu acceleration
  16. Query Optimization in Heterogeneous Cpu/gpu Environment for Time Series Databases
  17. A GPGPU-Based Acceleration of Fault-Tolerant Mlp Learnings
  18. Theano-based Large-Scale Visual Recognition with Multiple GPUs
  19. A Gpu Implementation of GoogLeNet

 

Gradient

  1. Accelerated gradient temporal difference learning algorithms
  2. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  3. Gradient-based Hyperparameter Optimization through Reversible Learning
  4. Convergence of gradient based pre-training in Denoising autoencoders

 

Gradient-Based

  1. Gradient-based Hyperparameter Optimization through Reversible Learning

 

Graph

  1. Graph-Based Supervised Automatic Target Detection
  2. Systems and methods for analyzing data using deep belief networks (dbn) and identifying a pattern in a graph

 

Graphical Model

  1. Hybrid Graphical Model for Semantic Image Segmentation

 

Graphics

  1. Deep Convolutional Inverse Graphics Network

 

Graphs

  1. Learning Word Representations from Relational Graphs

 

Grasping System

  1. Advanced Robotic Grasping System Using Deep Learning

 

Hadoop

  1. Design of Distributed Recommendation Engine Based on Hadoop and Mahout

 

Hand Pose

  1. Hands Deep in Deep Learning for Hand Pose Estimation

 

Handwriting Recognition

  1. Icfhr2014 Competition on Handwritten Text Recognition on tranScriptorium Datasets (HTRtS)
  2. Writer Adaptation using Bottleneck Features and Discriminative Linear Regression for Online Handwritten Chinese Character Recognition
  3. Deep-Belief-Network based Rescoring for Handwritten Word Recognition
  4. Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition
  5. A Tibetan Component Representation Learning Method for Online Handwritten Tibetan Character Recognition
  6. Managing Real-time Handwriting Recognition
  7. Real-time Stroke-order And Stroke-direction Independent Handwriting Recognition
  8. Multi-script Handwriting Recognition Using A Universal Recognizer

 

Handwritten

  1. On the Performance Improvement of Devanagri Handwritten Character Recognition
  2. DigiRec Proposal: Handwritten Digit Recognition in Hardware
  3. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

 

Handwritten Recognition

  1. Recognition of Multi-Stroke Based Online Handwritten Gurmukhi Aksharas

 

Hardware

  1. An Analog VLSI Deep Machine Learning Implementation
  2. Adaptive Many-Core Machines
  3. Motivation and Preliminaries
  4. Training itself: Mixed-signal training acceleration for memristor-based neural network.
  5. A Fully Pipelined FPGA Architecture of a Factored Restricted Boltzmann Machine Artificial Neural Network
  6. Performance Prediction by Deep Learning Methods for Semiconductor Manufacturing
  7. Back-Propagation Operation for Analog Neural Network Hardware with Synapse Components Having Hysteresis Characteristics
  8. Hardware-Amenable Structural Learning for Spike-based Pattern Classification using a Simple Model of Active Dendrites
  9. A Biological-Realtime Neuromorphic System in 28 nm Cmos using Low-Leakage Switched Capacitor Circuits
  10. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  11. DigiRec Proposal: Handwritten Digit Recognition in Hardware

 

Hash

  1. DeepHash: Getting Regularization, Depth and Fine-Tuning Right
  2. Deep learning with application to hashing
  3. Two Dimensional Hashing for Visual Tracking
  4. Shoe: Supervised Hashing with Output Embeddings
  5. Rank Subspace Learning for Compact Hash Codes

 

Hashing

  1. Inductive Transfer Deep Hashing for Image Retrieval
  2. Cross-Media Hashing with Neural Networks
  3. Deep learning with application to hashing
  4. Two Dimensional Hashing for Visual Tracking
  5. Shoe: Supervised Hashing with Output Embeddings

 

Healthcare

  1. Deep learning based imaging data completion for improved brain disease diagnosis
  2. A new 2.5 D representation for lymph node detection using random sets of deep convolutional neural network observations
  3. Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
  4. Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection
  5. Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods
  6. ML-o-scope: a diagnostic visualization system for deep machine learning pipelines
  7. Pruning Deep Neural Networks by Optimal Brain Damage
  8. DEEP LEARNING VIA STACKED SPARSE AUTOENCODERS FOR AUTOMATED VOXEL-WISE BRAIN PARCELLATION BASED ON FUNCTIONAL CONNECTIVITY (Thesis format: Monograph)
  9. Deep Learning for the Connectome
  10. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection
  11. Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks

 

Hearing Aid

  1. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid

 

Heart Failure

  1. Predicting Likelihood of Hospitalization with Subset-Filtered Emerging Patterns

 

Helicopter

  1. Machine Learning for Helicopter Dynamics Models

 

Hessian

  1. Subsampled Hessian Newton Methods for Su-pervised Learning

 

Hierarchical

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Hierarchical Recognition System for Target Recognition from Sparse Representations
  4. Learning invariant object recognition from temporal correlation in a hierarchical network
  5. Detectionn guided deconvolutional network for hierarchical feature learning
  6. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  7. Deep Hierarchical Parsing for Semantic Segmentation
  8. Hierarchical learning of grids of microtopics
  9. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  10. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

High-Dimensional Data

  1. A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling

 

Hmax

  1. A Hmax with Llc for visual recognition
  2. 6 On Handling Occlusions Using Hmax

 

Hmm

  1. Deep Neural Network-Hidden Markov Model Hybrid Systems
  2. Hidden Markov Models and the Variants
  3. A deep Hmm model for multiple keywords spotting in handwritten documents
  4. Soft context clustering for F0 modeling in HMM-based speech synthesis
  5. Audio-Concept Features and Hidden Markov Models for Multimedia Event Detection

 

Hmm-Based

  1. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network

 

Hough Transform

  1. Complex-Valued Hough Transforms for Circles

 

Human Behavior

  1. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  2. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

Human Pose

  1. An Effective Solution to Double Counting Problem in Human Pose Estimation

 

Human-Level

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  2. Human-level control through deep reinforcement learning

 

Hyperspectral

  1. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  2. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  3. Deep Convolutional Neural Networks for Hyperspectral Image Classification

 

Image Classification

  1. Combining Newton interpolation and deep learning for image classification
  2. DEFEATnet–A Deep Conventional Image Representation for Image Classification
  3. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  4. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  5. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  6. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  7. Image Classification Using Generative Neuro Evolution for Deep Learning
  8. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  9. Image classification using boosted local features with random orientation and location selection

 

Image De-Noising

  1. Image De-Noising Using Deep Learning

 

Image Parsing

  1. Adaptive Nonparametric Image Parsing

 

Image Quality

  1. No-reference image quality assessment with shearlet transform and deep neural Networks

 

Image Recognition

  1. Deep learning based imaging data completion for improved brain disease diagnosis
  2. A Deep Learning Pipeline for Image Understanding and Acoustic Modeling
  3. Learning a deep convolutional network for image super-resolution
  4. Cross-media relevance mining for evaluating text-based image search engine
  5. A deep learning approach to the classification of 3D CAD models
  6. Signature identification via efficient feature selection and GPU-based SVM classifier
  7. Handwritten Hangul recognition using deep convolutional neural networks
  8. ML-o-scope: a diagnostic visualization system for deep machine learning pipelines
  9. Deep Network Cascade for Image Super-resolution
  10. Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
  11. Deep Fragment Embeddings for Bidirectional Image Sentence Mapping
  12. Learning Rich Features from RGB-D Images for Object Detection and Segmentation
  13. Generic Object Detection With Dense Neural Patterns and Regionlets
  14. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  15. Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
  16. Using Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks for Partially Occluded Object Recognition
  17. $ N\^{} 4$-Fields: Neural Network Nearest Neighbor Fields for Image Transforms
  18. Single Image Super-resolution Reconstruction with Neural Network and Gaussian Process Regression
  19. Handwritten digit recognition using sparse deep architectures
  20. 3D ShapeNets for 2.5 D object recognition and Next-Best-View prediction
  21. Mining knowledge from clicks: MSR-Bing image retrieval challenge
  22. Fast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks
  23. A DEEP LEARNING APPROACH TO DOCUMENT IMAGE QUALITY ASSESSMENT
  24. Structured Prediction for Object Detection in Deep Neural Networks
  25. Multi-modal Feature Fusion for 3D Shape Recognition and Retrieval
  26. 3D Object Recognition using Convolutional Neural Networks with Transfer Learning between Input Channels
  27. CNN Features off-the-shelf: an Astounding Baseline for Recognition
  28. FEATURE GENERATION FOR QUANTIFICATION OF VISUAL SIMILARITY
  29. Mental Rotation by Optimizing Transforming Distance
  30. Effective Multi-Modal Retrieval based on Stacked Auto-Encoders
  31. Hierarchical kernel-based rotation and scale invariant similarity
  32. Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images
  33. Quantifying the Energy Efficiency of Object Recognition and Optical Flow
  34. Deep learning for image classification
  35. Local Feature Design Concepts, Classification, and Learning
  36. Object Detection and Viewpoint Estimation with Auto-masking Neural Network
  37. Large-Scale Scene Classification Using Gist Feature
  38. What you need to know about the state-of-the-art computational models of object-vision: A tour through the models
  39. Learning Sparse FRAME Models for Natural Image Patterns
  40. Surpassing Human-Level Face Verification Performance on LFW with GaussianFace
  41. Object recognition with hierarchical discriminant saliency networks
  42. Towards Real-Time Image Understanding with Convolutional Networks
  43. ImageNet Classification with Deep Convolutional Neural Networks
  44. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  45. Handwritten Hangul recognition using deep convolutional neural networks
  46. Joint Road Network Extraction From A Set Of High Resolution Satellite Images
  47. Self-taught Object Localization with Deep Networks
  48. Ibm research australia at lifeclef2014: Plant identification task
  49. MindLab at ImageCLEF 2014: Scalable Concept Image Annotation
  50. Sabanci-okan system at lifeclef 2014 plant identification competition
  51. Image classification via learning dissimilarity measure in non-euclidean spaces
  52. Compute Less to Get More: Using Orc to Improve Sparse Filtering
  53. Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks
  54. Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning
  55. Mlia at ImageCLFE 2014 Scalable Concept Image Annotation Challenge
  56. Random Cascaded-Regression Copse for Robust Facial Landmark Detection
  57. Contour Motion Estimation for Asynchronous Event-Driven Cameras
  58. Difference representation learning using stacked restricted Boltzmann machines for change detection in Sar images
  59. Object Classification via PCANet and Color Constancy Model
  60. The Application of Sift Image Matching in the Information Query Based on Mpi Acceleration
  61. Defect Detecting Technology Based on Machine Vision of Industrial Parts
  62. Neural Networks and Neuroscience-Inspired Computer Vision
  63. Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification
  64. 1-hkust: Object Detection in Ilsvrc 2014
  65. Domain Adaptive Neural Networks for Object Recognition
  66. Image Classification with A Deep Network Model based on Compressive Sensing
  67. Do More Dropouts in Pool5 Feature Maps for Better Object Detection
  68. Continuous gesture recognition from articulated poses
  69. Image-Based Analysis to Study Plant Infection with Human Pathogens
  70. Free-Form Region Description with Second-Order Pooling
  71. MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
  72. Hyper-Spectral Image Analysis with Partially-Latent Regression and Spatial Markov Dependencies
  73. Classifying Gray-scale Sar Images: Adeep Learning Approach
  74. Qr Code Localization Using Deep Neural Networks
  75. Localization of Visual Codes in the Dct Domain Using Deep Rectifier Neural Networks
  76. Deep Convolutional Neural Networks With An Application Towards Geospatial Object Recognition
  77. Vehicle License Plate Recognition With Random Convolutional Networks
  78. Human gesture recognition using three-dimensional integral imaging
  79. Saliency-guided deep framework for image quality assessment
  80. Helping robots see the big picture
  81. Exploiting the deep learning paradigm for recognizing human actions
  82. Deep Model for Classification of Hyperspectral image using Restricted Boltzmann Machine
  83. HAck: A system for the recognition of human actions by kernels of visual strings
  84. Explain Images with Multimodal Recurrent Neural Networks
  85. Deep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning
  86. Semantics of Visual Discrimination
  87. Multi-View Semi-Supervised Learning Based Image Annotation
  88. Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling
  89. Tensor index for large scale image retrieval
  90. Indirect shape analysis for 3d shape retrieval
  91. Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors
  92. A Simple Stochastic Algorithm for Structural Features Learning
  93. Deep supervised, but not unsupervised, models may explain It cortical representation
  94. Fully automatic segmentation of ultrasound common carotid artery images based on machine learning
  95. Automatic vertebrae localization, identification, and segmentation using deep learning and statistical models
  96. Deep Adaptive Networks for Visual Data Classification
  97. Coarse-to-Fine Minimization of Some Common Nonconvexities
  98. Multiple Spatio-Temporal Scales Neural Network for Contextual Visual Recognition of Human Actions
  99. Ghent University-iMinds at MediaEval 2014 Diverse Images: Adaptive Clustering with Deep Features
  100. Statistically Adaptive Image Denoising Based on Overcomplete Topographic Sparse Coding
  101. Nonlinear Supervised Locality Preserving Projections for Visual Pattern Discrimination
  102. Supervised feature learning via â„“2-norm regularized logistic regression for 3d object recognition
  103. Adaptive learning in a compartmental model of visual cortex-how feedback enables stable category learning and refinement
  104. Semi-Supervised Learning for Rgb-d Object Recognition
  105. Efficient image representation for object recognition via pivots selection
  106. Regularized Hierarchical Feature Learning with Non-Negative Sparsity and Selectivity for Image Classification
  107. Learning deep dynamical models from image pixels
  108. DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification
  109. Towards a Visual Turing Challenge
  110. Semantic parsing for priming object detection in indoors Rgb-d scenes
  111. Combining heterogenous features for 3d hand-held object recognition
  112. Rapid: Rating Pictorial Aesthetics using Deep Learning
  113. Fused one-vs-all mid-level features for fine-grained visual categorization
  114. DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks
  115. Cross Modal Deep Model and Gaussian Process Based Model for MSR-Bing Challenge
  116. Inductive Transfer Deep Hashing for Image Retrieval
  117. Error-Driven Incremental Learning in Deep Convolutional Neural Network for Large-Scale Image Classification
  118. Handwritten Digits Classification
  119. MatchBox: Indoor Image Matching via Box-like Scene Estimation
  120. Understanding image representations by measuring their equivariance and equivalence
  121. Hypercolumns for Object Segmentation and Fine-grained Localization
  122. The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
  123. A deep Hmm model for multiple keywords spotting in handwritten documents
  124. Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation
  125. Visual Scene Representations: Sufficiency, Minimality, Invariance and Approximations
  126. Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a Uav
  127. Image Recognition Using Convolutional Neural Networks
  128. Image Super-Resolution Using Deep Convolutional Networks
  129. Bikers are like tobacco shops, formal dressers are like suits: Recognizing Urban Tribes with Caffe
  130. Deep Image: Scaling up Image Recognition

 

Image Recognitionx

  1. Deep Convolutional Neural Network for Image Deconvolution

 

Image Representation

  1. DEFEATnet–A Deep Conventional Image Representation for Image Classification

 

Image Segmentation

  1. Early Hierarchical Contexts Learned by Convolutional Networks for Image Segmentation
  2. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
  3. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

 

Imagery

  1. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  2. Vehicle Detection in Aerial Imagery: A small target detection benchmark

 

Imaging

  1. Machine learning for transient discovery in Pan-STARRS1 difference imaging
  2. A spectrum of sharing: maximization of information content for brain imaging data
  3. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  4. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  5. Imaging and representation learning of solar radio spectrums for classification
  6. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Improvisation

  1. Machine Learning Applied to Musical Improvisation

 

Indexing

  1. A Dictionary Approach to Ebsd Indexing

 

Induction

  1. Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework

 

Inductive Bias

  1. Inductive Bias for Semi-supervised Extreme Learning Machine
  2. On the Inductive Bias of Dropout
  3. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning

 

Information

  1. Deep Learning and the Information Bottleneck Principle

 

Information Retrieval

  1. RankCNN: When learning to rank encounters the pseudo preference feedback
  2. Effective Multi-Modal Retrieval based on Stacked Auto-Encoders
  3. A compositional hierarchical model for music information retrieval
  4. Deep Sentence Embedding Using the Long Short Term Memory Network: Analysis and Application to Information Retrieval

 

Information Theory

  1. An Information Theoretic Approach to Quantifying Text Interestingness

 

Information-Theoretic

  1. Explicit knowledge extraction in information-theoretic supervised multi-layered Som

 

Infrastructure

  1. SPINDLE: SPINtronic deep learning engine for large-scale neuromorphic computing

 

Interpolation

  1. Combining Newton interpolation and deep learning for image classification

 

Invariant

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  2. Learning invariant object recognition from temporal correlation in a hierarchical network
  3. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  4. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Javascript

  1. MLitB: Machine Learning in the Browser

 

Kernel

  1. Training Generalized Feedforword Kernelized Neural Networks on Very Large Datasets for Regression Using Minimal-Enclosing-Ball Approximation
  2. On optimizing machine learning workloads via kernel fusion
  3. Hypothesis Testing with Kernel Embeddings on Big and Interdependent Data
  4. Deep Clustered Convolutional Kernels
  5. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  6. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Kernel Methods

  1. Kernel methods match deep neural networks on timit
  2. How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets

 

Kernels

  1. Riemannian Coding and Dictionary Learning: Kernels to the Rescue
  2. Deep Clustered Convolutional Kernels
  3. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels

 

Kickback

  1. Kickback cuts Backprop’s red-tape: Biologically plausible credit assignment in neural networks

 

Labeling

  1. Sequential Labeling with online Deep Learning

 

Lasso

  1. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Latent Structure

  1. Exploring Latent Structure in Data: Algorithms and Implementations

 

Lattice

  1. Permutohedral Lattice CNNs

 

Learning To Rank

  1. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization

 

Lecun

  1. Efficient Object Localization Using Convolutional Networks
  2. Unsupervised Learning of Spatiotemporally Coherent Metrics
  3. Deep learning with Elastic Averaging Sgd

 

Lfw

  1. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?

 

Linear Model

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Linear Models

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Log-Likelihood

  1. Accurate and Conservative Estimates of Mrf Log-likelihood using Reverse Annealing

 

Logistic

  1. Logistic Similarity Metric Learning For Face Verification

 

Long Short-Term Memory

  1. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …

 

Low Resolution

  1. Learning of Proto-object Representations via Fixations on Low Resolution

 

Lstm

  1. Text recognition using deep Blstm networks
  2. Compositional Distributional Semantics with Long Short Term Memory

 

Machine Translation

  1. Sequence to Sequence Learning with Neural Networks
  2. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
  3. Neural Machine Translation by Jointly Learning to Align and Translate
  4. AN AUTOENCODER WITH BILINGUAL SPARSE FEATURES FOR IMPROVED STATISTICAL MACHINE TRANSLATION
  5. Deep Learning for Natural Language Processing and Machine Translation
  6. Non-linear Learning for Statistical Machine Translation
  7. On Using Monolingual Corpora in Neural Machine Translation

 

Mahout

  1. Design of Distributed Recommendation Engine Based on Hadoop and Mahout

 

Mammogram Analysis

  1. Deep Structured learning for mass segmentation from Mammograms

 

Manufacturing

  1. Performance Prediction by Deep Learning Methods for Semiconductor Manufacturing

 

Matrix

  1. Supervised non-negative matrix factorization for audio source separation

 

Max Pooling

  1. Fractional Max-Pooling

 

Medical

  1. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  2. Applying deep learning techniques on medical corpora from the World Wide Web: a prototypical system and evaluation

 

Medical Records

  1. Adapting Linguistic Tools for the Analysis of Italian Medical Records

 

Medicine

  1. Deep learning of feature representation with multiple instance learning for medical image analysis
  2. Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
  3. Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection
  4. Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods
  5. ML-o-scope: a diagnostic visualization system for deep machine learning pipelines
  6. Pruning Deep Neural Networks by Optimal Brain Damage
  7. DEEP LEARNING VIA STACKED SPARSE AUTOENCODERS FOR AUTOMATED VOXEL-WISE BRAIN PARCELLATION BASED ON FUNCTIONAL CONNECTIVITY (Thesis format: Monograph)
  8. Deep Learning for the Connectome
  9. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection
  10. Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks
  11. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects
  12. A proteomic signature predicts response to a therapeutic vaccine in pancreas cancer; analysis from the Gi-4000-02 trial
  13. Fully automatic segmentation of ultrasound common carotid artery images based on machine learning
  14. Automatic vertebrae localization, identification, and segmentation using deep learning and statistical models
  15. Testing AutoTrace: A machine-learning approach to automated tongue contour data extraction
  16. Automatic Vaginal Bacteria Segmentation and Classification Based on Superpixel and Deep Learning
  17. Predicting Likelihood of Hospitalization with Subset-Filtered Emerging Patterns
  18. Deep Structured learning for mass segmentation from Mammograms
  19. Clinical Decision Analysis using Decision Tree
  20. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners
  21. Signal Processing in Next-Generation Prosthetics [Special Reports]
  22. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach
  23. Machine Learning for Medical Applications
  24. Adapting Linguistic Tools for the Analysis of Italian Medical Records
  25. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  26. Learning Deep Temporal Representations for Brain Decoding
  27. Cancerous Cell Detection Using Histopathological Image Analysis
  28. Dermoscopic Data Acquisition Employing Display Illumination
  29. Gesture-based Dermatologic Data Collection And Presentation
  30. Color Correction Arrangements For Dermoscopy
  31. Methods And Arrangements For Identifying Dermatological Diagnoses With Clinically Negligible Probabilties
  32. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  33. Automatic melanoma detection in dermatological images
  34. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Memory

  1. Memory Bounded Deep Convolutional Networks

 

Memristor

  1. Training itself: Mixed-signal training acceleration for memristor-based neural network.

 

Metric

  1. Obtaining Cross-modal Similarity Metric with Deep Neural Architecture

 

Metric Learning

  1. Deep metric learning using Triplet network
  2. Metric Learning

 

Microblog

  1. Multi-modal microblog classification via multi-task learning

 

Mimd

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Mine Detection

  1. Deep learning algorithms for detecting explosive hazards in ground penetrating radar data

 

Missing

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition

 

Mobile

  1. M2C: Energy efficient mobile cloud system for deep learning
  2. A 240 G-ops/s Mobile Coprocessor for Deep Neural Networks
  3. Brain-inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform
  4. An Efficient Implementation of Deep Convolutional Neural Networks on a Mobile Coprocessor
  5. Memory Access Optimized Scheduling Scheme for DCNNs on a Mobile Processor
  6. Contexto: lessons learned from mobile context inference
  7. Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors
  8. Smartphone based visible iris recognition using deep sparse filtering
  9. Non-parametric Bayesian Learning with Deep Learning Structure and Its Applications in Wireless Networks
  10. Travel Behavior Characterization Using Raw Accelerometer Data Collected from Smartphones
  11. Stt-snn: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks
  12. Can Deep Learning Revolutionize Mobile Sensing?
  13. Towards an Embodied Developing Vision System
  14. Keystroke Dynamics Advances for Mobile Devices Using Deep Neural Network
  15. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications

 

Monte Carlo

  1. Monte Carlo Integration Using Spatial Structure of Markov Random Field

 

Motion

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  3. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  4. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  5. Speech emotion recognition with unsupervised feature learning

 

Motion Detection

  1. Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition
  2. Contour Motion Estimation for Asynchronous Event-Driven Cameras

 

Motion Recognition

  1. MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation

 

Mri

  1. Brain Edge Detection
  2. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  3. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Multi-Label

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  2. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels

 

Multicore

  1. Adaptive Many-Core Machines
  2. Motivation and Preliminaries
  3. Training Large Scale Deep Neural Networks on the Intel Xeon Phi Many-core Coprocessor
  4. Machine Learning for Adaptive Many-Core Machines-A Practical Approach
  5. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Multimedia

  1. Multimedia Event Detection using Visual Features

 

Multimodal

  1. Multimodal Analytics and its Data Ecosystem
  2. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach
  3. Multimodal Transfer Deep Learning for Audio Visual Recognition

 

Music

  1. Chord Recognition with Stacked Denoising Autoencoders
  2. A compositional hierarchical model for music information retrieval
  3. Fusing Music and Video Modalities Using Multi-timescale Shared Representations
  4. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition
  5. Machine Learning Applied to Musical Improvisation

 

Natural Language Processing

  1. Adaptive multi-compositionality for recursive neural models with applications to sentiment analysis
  2. Adaptive recursive neural network for target-dependent twitter sentiment classification
  3. Modeling interestingness with deep neural networks
  4. Deep convolutional neural networks for sentiment analysis of short texts
  5. Learning Character-level Representations for Part-of-Speech Tagging
  6. Language Modeling with Sum-Product Networks
  7. Learning Sparse Recurrent Neural Networks in Language Modeling
  8. Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model
  9. Think Positive: Towards Twitter Sentiment Analysis from Scratch
  10. A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words
  11. Max-Margin Tensor Neural Network for Chinese Word Segmentation
  12. Query expansion for mixed-script information retrieval
  13. Query Expansion for Multi-script Information Retrieval
  14. AN AUTOENCODER WITH BILINGUAL SPARSE FEATURES FOR IMPROVED STATISTICAL MACHINE TRANSLATION
  15. Learning Distributed Representations of Natural Language Text with Artificial Neural Networks
  16. Modeling Newswire Events using Neural Networks for Anomaly Detection
  17. A semantic matching energy function for learning with multi-relational data
  18. Modelling ‚Visualising and Summarising Documents with a Single Convolutional Neural Network
  19. Introduction to Word2vec and its application to find predominant word senses
  20. Rc-net: A General Framework for Incorporating Knowledge into Word Representations
  21. Analyzing sparse dictionaries for online learning with kernels
  22. Coupled Projections for Semi-supervised Adaptation of Dictionaries
  23. Automatic Arabic diacritics restoration based on deep nets
  24. Transduction Recursive Auto-Associative Memory: Learning Bilingual Compositional Distributed Vector Representations of Inversion Transduction Grammars
  25. Learning Bilingual Embedding Model for Cross-Language Sentiment Classification
  26. Fuzzy Subjective Sentiment Phrases: A Context Sensitive and Self-Maintaining Sentiment Lexicon
  27. Deep Learning for Natural Language Processing and Machine Translation
  28. Deep Recursive Neural Networks for Compositionality in Language
  29. Text Mining with the Stanford CoreNLP
  30. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
  31. From Captions to Visual Concepts and Back
  32. Show and Tell: A Neural Image Caption Generator
  33. Deep Belief Networks and Biomedical Text Categorisation
  34. Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
  35. Deep Learning for Answer Sentence Selection
  36. Improving relation descriptor extraction with word embeddings and cluster features
  37. Practice in Synonym Extraction at Large Scale
  38. Reading Text in the Wild with Convolutional Neural Networks
  39. Learning Word Representations from Relational Graphs
  40. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  41. An Information Theoretic Approach to Quantifying Text Interestingness
  42. Adapting Linguistic Tools for the Analysis of Italian Medical Records
  43. Translating Videos to Natural Language Using Deep Recurrent Neural Networks
  44. Data collection and language understanding of food descriptions
  45. Cnu System in Ntcir-11 IMine Task
  46. Tuta1 at the Ntcir-11 IMine Task
  47. Deep Learning for Web Search and Natural Language Processing
  48. Open Domain Question Answering via Semantic Enrichment
  49. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  50. Syntax-based Deep Matching of Short Texts
  51. Deep Multilingual Correlation for Improved Word Embeddings

 

Network

  1. Detection of retransmissions in 10G Ethernet using GPUs
  2. Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network

 

Network Analysis

  1. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data

 

Network Congestion

  1. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

 

Networking

  1. Can Congestion in Data Center Networks Be Predicted By Of Time Of Day?

 

Neuromorphic

  1. SPINDLE: SPINtronic deep learning engine for large-scale neuromorphic computing
  2. Thermodynamic-RAM Technology Stack
  3. A neuromorphic categorization system with Online Sequential Extreme Learning
  4. A Biological-Realtime Neuromorphic System in 28 nm Cmos using Low-Leakage Switched Capacitor Circuits

 

Neuron

  1. Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels

 

Neuroscience

  1. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom

 

Newton

  1. Combining Newton interpolation and deep learning for image classification
  2. Subsampled Hessian Newton Methods for Su-pervised Learning

 

Noise

  1. Analyzing noise in autoencoders and deep networks
  2. Scheduled denoising autoencoders
  3. Chord Recognition with Stacked Denoising Autoencoders
  4. Regularizing Recurrent Networks-On Injected Noise and Norm-based Methods
  5. Statistically Adaptive Image Denoising Based on Overcomplete Topographic Sparse Coding
  6. Training Deep Neural Networks on Noisy Labels with Bootstrapping

 

Noiseness

  1. A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development
  2. Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments
  3. Feature Learning from Incomplete Eeg with Denoising Autoencoder

 

Noisy

  1. Noisy Training for Deep Neural Networks in Speech Recognition

 

Noisy Data

  1. Learning from Noisy Labels with Deep Neural Networks

 

Non-Convex

  1. Online Bandit Learning for a Special Class of Non-convex Losses
  2. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  3. On Graduated Optimization for Stochastic Non-Convex Problems

 

Non-Euclidian

  1. Image classification via learning dissimilarity measure in non-euclidean spaces

 

Numerical

  1. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework

 

Numerics

  1. Accuracy evaluation of deep belief networks with fixed-point arithmetic
  2. Low precision arithmetic for deep learning

 

Object Classification

  1. Deep Roto-Translation Scattering for Object Classification

 

Object Detection

  1. Unsupervised Learning of Semantics of Object Detections for Scene Categorization
  2. DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection
  3. Background Prior Based Salient Object Detection via Deep Reconstruction Residual
  4. View-independent object detection using shared local features

 

Object Localization

  1. Efficient Object Localization Using Convolutional Networks
  2. Self-Taught Object Localization with Deep Networks

 

Object Recognition

  1. Efficient Learning of Sparse, Distributed, Convolutional Feature Representations for Object Recognition
  2. Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection
  3. Analysis of Multilayer Neural Networks for Object Recognition
  4. Real-time object recognition and orientation estimation using an event-based camera and Cnn
  5. HFirst: A Temporal Approach to Object Recognition
  6. Learning invariant object recognition from temporal correlation in a hierarchical network
  7. Learning Descriptors for Object Recognition and 3d Pose Estimation
  8. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  9. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  10. Subset based deep learning for Rgb-d object recognition

 

Object Reconstruction

  1. Virtual View Networks for Object Reconstruction

 

Occlusion

  1. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  2. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  3. 6 On Handling Occlusions Using Hmax

 

Occlusions

  1. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  2. 6 On Handling Occlusions Using Hmax

 

Online Learning

  1. Analyzing sparse dictionaries for online learning with kernels
  2. Error-Driven Incremental Learning in Deep Convolutional Neural Network for Large-Scale Image Classification

 

Open Source

  1. Introducing CURRENNT–the Munich open-source Cuda RecurREnt Neural Network Toolkit

 

Optimization

  1. Query Optimization in Heterogeneous Cpu/gpu Environment for Time Series Databases
  2. The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks
  3. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates
  4. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
  5. Convolutional Neural Networks at Constrained Time Cost
  6. Memory Bounded Deep Convolutional Networks
  7. Sparse Representations, Numerical Linear Algebra, and Optimization
  8. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM
  9. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators
  10. Gradient-based Hyperparameter Optimization through Reversible Learning
  11. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  12. Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
  13. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework
  14. Scalable Bayesian Optimization Using Deep Neural Networks
  15. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  16. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters
  17. On Graduated Optimization for Stochastic Non-Convex Problems

 

Optimized

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. Jointly Optimized Regressors for Image Super-resolution

 

Orientation Estimation

  1. Real-time object recognition and orientation estimation using an event-based camera and Cnn

 

Over-Sampling

  1. Over-Sampling in a Deep Neural Network

 

Overview

  1. Deep Learning in Neural Networks: An Overview
  2. Draft: Deep Learning in Neural Networks: An Overview
  3. Big Data Deep Learning: Challenges and Perspectives
  4. Neural Networks: A Review
  5. Deep Learning
  6. An Anarchy of Methods: Current Trends in How Intelligence Is Abstracted in Ai
  7. An Overview of Deep Generative Models
  8. An Overview of Color Name Applications in Computer Vision
  9. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Pancreas

  1. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Parallel

  1. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning

 

Parallelization

  1. On Parallelizability of Stochastic Gradient Descent for Speech DNNs
  2. GPUs: High-performance Accelerators for Parallel Applications: The multicore transformation (Ubiquity symposium)
  3. One weird trick for parallelizing convolutional neural networks
  4. Parallel batch pattern training algorithm for deep neural network
  5. The Application of Sift Image Matching in the Information Query Based on Mpi Acceleration
  6. Gaussian Process Models with Parallelization and Gpu acceleration
  7. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Parameter

  1. Continuous Hyper-parameter Learning for Support Vector Machines
  2. Gradient-based Hyperparameter Optimization through Reversible Learning
  3. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  4. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Parameter Tuning

  1. Predicting parameters in deep learning

 

Parameters

  1. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  2. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Parsing

  1. Deep Human Parsing with Active Template Regression
  2. Deep Hierarchical Parsing for Semantic Segmentation

 

Part-Of-Speech

  1. Learning Character-level Representations for Part-of-Speech Tagging

 

Pca

  1. From neural Pca to deep unsupervised learning

 

Pedestrian Detection

  1. Pedestrian Detection Based on Multi-Stage Unsupervised Learning
  2. Pedestrian Detection aided by Deep Learning Semantic Tasks
  3. Pedestrian Detection From Salient Regions
  4. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  5. Taking a Deeper Look at Pedestrians
  6. Filtered Channel Features for Pedestrian Detection
  7. Pedestrian Detection Via Pca Filters Based Convolutional Channel

 

Perception

  1. Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction

 

Perceptron

  1. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems

 

Performance Improvement

  1. Improving Deep Neural Network Performance by Reusing Features Trained with Transductive Transference
  2. Speeding up Convolutional Neural Networks with Low Rank Expansions
  3. Improve Performance in Deep Neural Networks:(1) Cost Functions, and (2) Reusable learning
  4. Improving Transfer Learning Accuracy by Reusing Stacked Denoising Autoencoders
  5. Alternate Layer Sparsity and Intermediate Fine-tuning for Deep Autoencoders
  6. Transfer of Learning Across Deep Networks to Improve Performance in Problems with Few Labelled Data
  7. Acceleration Strategies for Speech Recognition Based on Deep Neural Networks
  8. On the Performance Improvement of Devanagri Handwritten Character Recognition

 

Personalize

  1. Principles of Explanatory Debugging to Personalize Interactive Machine Learning

 

Phoneme

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition

 

Photo Adjustment

  1. Automatic Photo Adjustment Using Deep Learning

 

Photonic

  1. Photonic Delay Systems as Machine Learning Implementations

 

Physics

  1. Searching for exotic particles in high-energy physics with deep learning
  2. Deep Learning in High-Energy Physics: Improving the Search for Exotic Particles
  3. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  4. Enhanced Higgs Boson to τ+ τ− Search with Deep Learning

 

Pinterest

  1. Predicting Pinterest: Automating a distributed human computation

 

Plankton

  1. Predicting ocean health, one plankton at a time

 

Planning

  1. Accurate localized short term weather prediction for renewables planning
  2. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Platform

  1. Mariana: Tencent Deep Learning Platform and its Applications
  2. DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
  3. Implementation and evaluation of deep neural networks (DNN) on mainstream heterogeneous systems
  4. A scalable and topology configurable protocol for distributed parameter synchronization
  5. Large scale recurrent neural network on GPU
  6. Distributed Asynchronous Optimization of Convolutional Neural Networks
  7. Kaldi+ PDNN: Building DNN-based ASR Systems with Kaldi and PDNN
  8. Improving deep neural networks for LVCSR using dropout and shrinking structure
  9. Deep Epitomic Convolutional Neural Networks
  10. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  11. A brief survey on deep belief networks and introducing a new object oriented MATLAB toolbox (DeeBNet)
  12. Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning
  13. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach

 

Pooling

  1. Fractional Max-Pooling
  2. Domain-Size Pooling in Local Descriptors: Dsp-sift

 

Pose

  1. An Effective Solution to Double Counting Problem in Human Pose Estimation
  2. Hands Deep in Deep Learning for Hand Pose Estimation
  3. Inferring 3d Object Pose in Rgb-d Images
  4. Emeuro: a framework for generating multi-purpose accelerators via deep learning
  5. Learning Descriptors for Object Recognition and 3d Pose Estimation
  6. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Pose Recognition

  1. Real-time continuous pose recovery of human hands using convolutional networks

 

Posture Recognition

  1. Deep learning for posture analysis in fall detection
  2. A Real-time Hand Posture Recognition System Using Deep Neural Networks
  3. A Biologically Inspired Human Posture Recognition System

 

Pre-Training

  1. Statistical-mechanical analysis of pre-training and fine tuning in deep learning
  2. Convergence of gradient based pre-training in Denoising autoencoders

 

Predicting

  1. Where am I? Predicting Montreal Neighbourhoods from Google Street View Images
  2. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  3. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  4. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  5. Predicting the Quality of User-Generated Answers Using Co-Training in Community-based Question Answering Portals
  6. Predicting Entry-Level Categories
  7. Predicting Pinterest: Automating a distributed human computation
  8. Predicting ocean health, one plankton at a time
  9. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Prediction

  1. Accurate localized short term weather prediction for renewables planning
  2. Retrieval Term Prediction Using Deep Belief Networks
  3. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  4. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  5. Feature maps driven no-reference image quality prediction of authentically distorted images
  6. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  7. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  8. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Predictive Modelling

  1. Hybrid Predictive Model For Enhancing Prosodic Expressiveness

 

Predictors

  1. Learning Hypergraph-regularized Attribute Predictors

 

Pretraining

  1. Assessment of Electrocardiograms with Pretraining and Shallow Networks

 

Probabilistic

  1. Deep Transform: Cocktail Party Source Separation via Probabilistic Re-Synthesis

 

Processor

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Programming Language Processing

  1. Tbcnn: A Tree-Based Convolutional Neural Network for Programming Language Processing

 

Prosthetics

  1. Signal Processing in Next-Generation Prosthetics [Special Reports]

 

Proteinomics

  1. Possible computational filter to detect proteins associated to influenza A subtype H1n1.
  2. lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning
  3. Fast loop modeling for protein structures

 

Python

  1. Theano-based Large-Scale Visual Recognition with Multiple GPUs

 

Quality

  1. Deep Learning For Objective Quality Assessment Of 3d Images
  2. Parsing Occluded People by Flexible Compositions
  3. Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
  4. No-reference image quality assessment with shearlet transform and deep neural Networks
  5. On the Stability of Deep Networks
  6. Software Quality Evaluation of Face Recognition APIs & Libraries
  7. An Innovative Svm for Wheat Seed Quality Estimation⋆

 

Quantum

  1. Quantum Energy Regression using Scattering Transforms

 

Quantum Computing

  1. An introduction to quantum machine learning
  2. An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
  3. Quantum Deep Learning
  4. Simulating a perceptron on a quantum computer
  5. Majorana Zero Modes and Topological Quantum Computation

 

Quantum Deep Learning

  1. Quantum Deep Learning
  2. Simulating a perceptron on a quantum computer

 

Random Field

  1. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  2. Conditional Random Fields as Recurrent Neural Networks

 

Random Fields

  1. Conditional Random Fields as Recurrent Neural Networks

 

Random Forests

  1. Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?
  2. Random Forests Can Hash

 

Ranking

  1. Multiple level visual semantic fusion method for image re-ranking
  2. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization

 

Rbm

  1. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  2. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Recommendation Systems

  1. A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems

 

Recommender Systems

  1. Improving Content-based and Hybrid Music Recommendation using Deep Learning
  2. Collaborative Deep Learning for Recommender Systems
  3. Cars2: Learning Context-aware Representations for Context-aware Recommendations
  4. Deep Exponential Families

 

Rectified

  1. Rectified Factor Networks

 

Rectifiers

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

 

Rectifiers:

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

 

Recurrant Neural Networks

  1. Regularizing Recurrent Networks-On Injected Noise and Norm-based Methods
  2. Translating Videos to Natural Language Using Deep Recurrent Neural Networks

 

Recurrent

  1. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  2. Conditional Random Fields as Recurrent Neural Networks
  3. Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
  4. Draw: A Recurrent Neural Network For Image Generation
  5. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  6. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

 

Recurrent Nets

  1. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

 

Recurrent Networks

  1. Recurrent Neural Networks and Related Models

 

Recurrent Neural Networks

  1. Learning to Execute

 

Regression

  1. A Deep and Stable Extreme Learning Approach for Classification and Regression
  2. Transparent-supported radiance regression function
  3. Random Bits Regression: a Strong General Predictor for Big Data
  4. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  5. Quantum Energy Regression using Scattering Transforms
  6. Deep Human Parsing with Active Template Regression
  7. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech

 

Regularization

  1. Manifold Regularized Deep Neural Networks
  2. A comparison of dropout and weight decay for regularizing deep neural networks
  3. A Survey of Regularization Methods for Deep Neural Network
  4. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
  5. Neural Network Regularization via Robust Weight Factorization
  6. DeepHash: Getting Regularization, Depth and Fine-Tuning Right
  7. Mask selective regularization for restricted Boltzmann machines

 

Reinforcement Learning

  1. Evolving deep unsupervised convolutional networks for vision-based reinforcement learning
  2. Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning
  3. Hierarchical reinforcement learning in a biologically plausible neural architecture
  4. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  5. Human-level control through deep reinforcement learning
  6. Deep Reinforcement Learning for constructing meaning by ‘babbling’
  7. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Reliability

  1. A GPGPU-Based Acceleration of Fault-Tolerant Mlp Learnings

 

Representation

  1. Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects

 

Representation Learning

  1. Deep Representation Learning with Target Coding Supplementary Material
  2. Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning
  3. Training Stacked Denoising Autoencoders for Representation Learning
  4. End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning
  5. Imaging and representation learning of solar radio spectrums for classification
  6. Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification
  7. Unsupervised domain adaptation via representation learning and adaptive classifier learning
  8. On Invariance and Selectivity in Representation Learning

 

Restricted Boltzmann Machine

  1. To be Bernoulli or to be Gaussian, for a Restricted Boltzmann Machine
  2. Deep neural network based load forecast
  3. Expected energy-based restricted Boltzmann machine for classification
  4. A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development
  5. Deep Tempering
  6. A Novel Inference of a Restricted Boltzmann Machine
  7. Deep Model for Classification of Hyperspectral image using Restricted Boltzmann Machine
  8. Classification Restricted Boltzmann Machine for comprehensible credit scoring model
  9. Deep Correspondence Restricted Boltzmann Machine for Cross-modal Retrieval
  10. A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling
  11. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  12. Stochastic Spectral Descent for Restricted Boltzmann Machines
  13. Advanced Mean Field Theory of Restricted Boltzmann Machine
  14. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  15. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  16. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  17. Mask selective regularization for restricted Boltzmann machines
  18. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Restricted Boltzmann Machines

  1. Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition
  2. Learning ensemble classifiers via restricted Boltzmann machines
  3. Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks
  4. A Fully Pipelined FPGA Architecture of a Factored Restricted Boltzmann Machine Artificial Neural Network
  5. Difference representation learning using stacked restricted Boltzmann machines for change detection in Sar images
  6. Maximum Reconstruction Probability Training Of Restricted Boltzmann Machines With Auxiliary Function Approach
  7. High-Order Semi-RBMs and Deep Gated Neural Networks for Feature Interaction Identification and Non-Linear Semantic Indexing
  8. Periocular Recognition using Unsupervised Convolutional Rbm Feature Learning
  9. A 3d model recognition mechanism based on deep boltzmann machines
  10. Scalable Learning for Restricted Boltzmann Machines
  11. Atomic Energy Models For Machine Learning: Atomic Restricted Boltzmann Machines
  12. A Distributed Implementation of Training the Restricted Boltzmann Machine
  13. Energy Based Models and Boltzmann Machines (Cont.)
  14. Deep Narrow Boltzmann Machines are Universal Approximators
  15. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
  16. An automatic setting for training restricted boltzmann machine
  17. An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
  18. Restricted Boltzmann Machines with Svm for Object Recognition⋆
  19. Voice Conversion Using Rnn Pre-Trained by Recurrent Temporal Restricted Boltzmann Machines
  20. Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning
  21. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  22. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  23. Stochastic Spectral Descent for Restricted Boltzmann Machines
  24. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  25. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  26. Mask selective regularization for restricted Boltzmann machines
  27. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Restricted Bolzmann Machines

  1. L_1-regularized Boltzmann machine learning using majorizer minimization

 

Retail

  1. Forecasting And Inventory Performance In Direct-store Delivery Supply Chain: Case Of Retailer In Serbia

 

Retinal Images

  1. Diagnosis Of Diabetic Retinopathy By Segmentation Of Blood Vessels In Retinal Images

 

Reverse Annealing

  1. Accurate and Conservative Estimates of Mrf Log-likelihood using Reverse Annealing

 

Review

  1. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  2. A Review of Methods for the Calculation of Solution Free Energies and the Modelling of Systems in Solution
  3. Unsupervised Deep Learning: A Short Review
  4. Efficient Machine Learning for Big Data: A Review

 

Risk Minimization

  1. Advances in Empirical Risk Minimization for Image Analysis and Pattern Recognition

 

Road Detection

  1. Adaptive Road Detection via Context-aware Label Transfer

 

Robot

  1. Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web
  2. Robotic Grasping System Using Convolutional Neural Networks
  3. Advanced Robotic Grasping System Using Deep Learning
  4. A survey of research on cloud robotics and automation
  5. Robust face recognition via transfer learning for robot partner
  6. Robot team learning enhancement using Human Advice
  7. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  8. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Robotics

  1. Multimodal integration learning of robot behavior using deep neural networks
  2. Survey and Implementation of Computer Vision Techniques for Humanoid Robots
  3. Helping robots see the big picture
  4. Deep learning for detecting robotic grasps
  5. Control In A Safe Set: Addressing Safety In Human-robot Interactions
  6. A survey of research on cloud robotics and automation
  7. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Robust

  1. Robust face recognition via transfer learning for robot partner
  2. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  3. Robust Tracking via Convolutional Networks without Learning
  4. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  5. Robust Excitation-based Features For Automatic Speech Recognition
  6. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  7. Supervised descent method with low rank and sparsity constraints for robust face alignment
  8. Robust people counting using sparse representation and random projection
  9. Simple, Accurate, and Robust Nonparametric Blind Super-Resolution

 

Salient

  1. Background Prior Based Salient Object Detection via Deep Reconstruction Residual

 

Sampling

  1. Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?

 

Sar Data

  1. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks

 

Scalability

  1. Scaling Distributed Machine Learning with the Parameter Server
  2. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
  3. Scalable, High-Quality Object Detection
  4. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  5. DeepSpeech: Scaling up end-to-end speech recognition

 

Scene Classification

  1. Scene Classification Based on Single-layer Sae and Svm
  2. Dynamic texture and scene classification by transferring deep image features
  3. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  4. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks

 

Scene Recognition

  1. Deep Deconvolutional Networks for Scene Parsing
  2. Scene Recognition Using Mid-level features from Cnn
  3. Scene Recognition
  4. Scene Recognition by Manifold Regularized Deep Learning Architecture

 

Scheduling

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Score Function

  1. Score Function Features for Discriminative Learning: Matrix and Tensor Framework
  2. Score Function Features for Discriminative Learning

 

Sda

  1. Two-Stage Learning to Predict Human Eye Fixations via SDAEs

 

Search

  1. Query expansion for mixed-script information retrieval
  2. Query Expansion for Multi-script Information Retrieval
  3. A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval
  4. Enhanced Higgs to $\ tau^+\ tau^-$ Searches with Deep Learning
  5. Implicitly Learning a User Interest Profile for Personalization of Web Search Using Collaborative Filtering
  6. Research on deep neural network’s hidden layers in phoneme recognition
  7. Cross-modal Retrieval with Correspondence Autoencoder
  8. Deep Search with Attribute-aware Deep Network
  9. Deep learning for real-time Atari game play using offline Monte-Carlo tree search planning
  10. Beginning at the End: The outcome spaces framework to guide purposive transdisciplinary research
  11. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
  12. The Research of Event Detection and Characterization Technology of Ticket Gate in the Urban Rapid Rail Transit
  13. A survey of research on cloud robotics and automation
  14. Entity-centric search: querying by entities and for entities
  15. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  16. Deep Learning for Web Search and Natural Language Processing
  17. Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research
  18. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”
  19. Enhanced Higgs Boson to τ+ τ− Search with Deep Learning
  20. Threshold concepts in the Scholarship of Teaching and Learning: a phenomenological study of educational leaders in a Canadian research-intensive university

 

Security

  1. Deep Learning of Behaviors for Security
  2. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”

 

Segmentation

  1. Fully Convolutional Networks for Semantic Segmentation
  2. Fully Convolutional Neural Networks for Crowd Segmentation
  3. Hypercolumns for Object Segmentation and Fine-grained Localization
  4. Deep convolutional filter banks for texture recognition and segmentation
  5. Hybrid Graphical Model for Semantic Image Segmentation
  6. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  7. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  8. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  9. Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation
  10. Deep Hierarchical Parsing for Semantic Segmentation
  11. Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric Mr images
  12. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Self-Informed

  1. Self-informed neural network structure learning

 

Semantic

  1. Cnu System in Ntcir-11 IMine Task
  2. Tuta1 at the Ntcir-11 IMine Task
  3. Hybrid Graphical Model for Semantic Image Segmentation
  4. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  5. Open Domain Question Answering via Semantic Enrichment
  6. Learning Semantic Hierarchies: A Continuous Vector Space Approach
  7. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  8. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  9. Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation
  10. Compositional Distributional Semantics with Long Short Term Memory
  11. Deep Hierarchical Parsing for Semantic Segmentation
  12. Deep Structured Semantic Model Produced Using Click-Through Data
  13. Learning Document Semantic Representation with Hybrid Deep Belief Network
  14. Lig at TRECVid 2014: Semantic Indexing

 

Semantic Indexing

  1. Lig at TRECVid 2014: Semantic Indexing

 

Semantics

  1. Learning Multi-Relational Semantics Using Neural-Embedding Models
  2. Compositional Distributional Semantics with Long Short Term Memory

 

Semantix Indexing

  1. High-Order Semi-RBMs and Deep Gated Neural Networks for Feature Interaction Identification and Non-Linear Semantic Indexing

 

Semi-Supervised

  1. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery
  2. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation

 

Sensor Data

  1. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  2. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data

 

Sensory

  1. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework

 

Sentiment

  1. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  2. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Sentiment Analysis

  1. Adaptive multi-compositionality for recursive neural models with applications to sentiment analysis
  2. Adaptive recursive neural network for target-dependent twitter sentiment classification
  3. Deep convolutional neural networks for sentiment analysis of short texts
  4. Recursive Deep Learning for Sentiment Analysis over Social Data
  5. Learning Bilingual Embedding Model for Cross-Language Sentiment Classification
  6. Visual Sentiment Prediction with Deep Convolutional Neural Networks
  7. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Sequence Learning

  1. Sequence to Sequence Learning with Neural Networks
  2. On the Problem of Features Variability in Sequence Learning Problems

 

Sequence Modelling

  1. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

 

Shape Classification

  1. Iterative 3d shape classification by online metric learning

 

Shearlet Transform

  1. No-reference image quality assessment with shearlet transform and deep neural Networks

 

Sigmoid

  1. Learning Deep Sigmoid Belief Networks with Data Augmentation

 

Sign Language

  1. Sign language recognition using convolutional neural networks

 

Signal Processing

  1. Signal Processing in Next-Generation Prosthetics [Special Reports]

 

Similarity Learning

  1. Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation

 

Simplicity

  1. Striving for Simplicity: The All Convolutional Net

 

Simulation

  1. GPU Accelerated Computation and Real-time Rendering of Cellular Automata Model for Spatial Simulation
  2. Using High-fidelity Simulation as a Learning Strategy in an Undergraduate Intensive Care Course
  3. Entrepreneurship Support Based on Mixed Bio-Artificial Neural Network Simulator (esbbann)

 

Singular Value Decomposition

  1. An Optimization of Deep Neural Networks in Asr using Singular Value Decomposition

 

Sketch Recognition

  1. Freehand Sketch Recognition Using Deep Features
  2. Deep Neural Networks for Sketch Recognition

 

Smart City

  1. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City

 

Smart Homes

  1. Recognizing human activity in smart home using deep learning algorithm

 

Smoothing

  1. Single image super-resolution via L0 image smoothing
  2. Single Image Super-Resolution via Image Smoothing

 

Social

  1. Detecting spammers on social Networks
  2. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features

 

Social Network

  1. Deep learning-based target customer position extraction on social network

 

Soft Computing

  1. An Evaluation of Deep Learning Miniature Concerning in Soft Computing

 

Softmax

  1. Quaternion softmax classifier
  2. An Image Retrieval Method for Binary Images Based on Dbn and Softmax Classifier

 

Software

  1. Software Quality Evaluation of Face Recognition APIs & Libraries

 

Sosial Network

  1. Recursive Deep Learning for Sentiment Analysis over Social Data

 

Sound

  1. Recognition Of Acoustic Events Using Deep Neural Networks
  2. Audio Concept Classification With Hierarchical Deep Neural Networks
  3. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training
  4. Estimating Tract Variables from Acoustics via Neural Networks
  5. Supervised non-negative matrix factorization for audio source separation
  6. Multilabel Sound Event Classification with Neural Networks
  7. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition

 

Sound Retrieval

  1. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks

 

Spam

  1. Spammer detection on Sina Micro-Blog
  2. Detecting spammers on social Networks

 

Sparse

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Hierarchical Recognition System for Target Recognition from Sparse Representations
  4. Sparse Neural Networks
  5. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  6. Robust people counting using sparse representation and random projection

 

Sparseness

  1. A Winner-Take-All Method for Training Sparse Convolutional Autoencoders
  2. DEEP LEARNING VIA STACKED SPARSE AUTOENCODERS FOR AUTOMATED VOXEL-WISE BRAIN PARCELLATION BASED ON FUNCTIONAL CONNECTIVITY (Thesis format: Monograph)
  3. Exploiting sparseness in training deep neural networks
  4. Alternate Layer Sparsity and Intermediate Fine-tuning for Deep Autoencoders
  5. A linear approach for sparse coding by a two-layer neural network
  6. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  7. Compute Less to Get More: Using Orc to Improve Sparse Filtering
  8. Spatially-sparse convolutional neural networks
  9. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  10. Analyzing sparse dictionaries for online learning with kernels
  11. Sparse Representations, Numerical Linear Algebra, and Optimization
  12. Provable Methods for Training Neural Networks with Sparse Connectivity
  13. Sparse Deep Stacking Network for Image Classification

 

Sparsity

  1. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  2. Supervised descent method with low rank and sparsity constraints for robust face alignment

 

Spatial

  1. The Spatial Complexity of Inhomogeneous Multi-layer Neural Networks
  2. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  3. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  4. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  5. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  6. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  7. Learning by Observation Using Qualitative Spatial Relations

 

Spatial Planning

  1. Systems View on Spatial Planning and Perception Based on Invariants in Agent-Environment Dynamics

 

Spatially

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization

 

Spatio-Temporal

  1. Learning spatio-temporal features for action recognition from the side of the video
  2. Spatio-Temporal Moving Object Proposals
  3. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  4. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  5. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  6. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism

 

Spectral

  1. Stochastic Spectral Descent for Restricted Boltzmann Machines
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  4. Deep Convolutional Neural Networks for Hyperspectral Image Classification

 

Spectral Classification

  1. Spectral classification using convolutional neural networks

 

Speech

  1. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  5. Noisy Training for Deep Neural Networks in Speech Recognition
  6. Deep Multimodal Learning for Audio-Visual Speech Recognition
  7. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  8. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network
  9. Robust Excitation-based Features For Automatic Speech Recognition
  10. Machine Learning in Automatic Speech Recognition: A Survey
  11. Deep learning for speech classification and speaker recognition
  12. Speech Separation based on Deep Belief Network
  13. Speech emotion recognition with unsupervised feature learning
  14. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech

 

Speech Recognition

  1. Should deep neural nets have ears? The role of auditory features in deep learning approaches
  2. Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition
  3. Deep learning vector quantization for acoustic information retrieval
  4. A Deep Learning Pipeline for Image Understanding and Acoustic Modeling
  5. Parallel Deep Neural Network Training for LVCSR Tasks using Blue Gene/Q
  6. 1-Bit Stochastic Gradient Descent and its Application to Data-Parallel Distributed Training of Speech DNNs
  7. Deep Learning for Emotional Speech Recognition
  8. Improving deep neural network acoustic models using generalized maxout networks
  9. RASR/NN: The RWTH neural network toolkit for speech recognition
  10. On Parallelizability of Stochastic Gradient Descent for Speech DNNs
  11. First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs
  12. A historical perspective of speech recognition
  13. Improving deep neural networks for LVCSR using dropout and shrinking structure
  14. A comparison of two optimization techniques for sequence discriminative training of deep neural networks
  15. Using Deep Belief Networks for Vector-Based Speaker Recognition
  16. Fine context, low-rank, softplus deep neural networks for mobile speech recognition
  17. Statistical Parametric Speech Synthesis using Weighted Multi-distribution Deep Belief Network
  18. Boundary Contraction Training for Acoustic Models based on Discrete Deep Neural Networks
  19. Contrastive auto-encoder for phoneme recognition
  20. Deep Learning of Orthographic Representations in Baboons
  21. Speaker adaptation of deep neural network based on discriminant codes
  22. Deep learning of split temporal context for automatic speech recognition
  23. Deep Generative and Discriminative Models for Speech Recognition
  24. Spoken emotion recognition using deep learning
  25. RASR/NN: THE RWTH NEURAL NETWORK TOOLKIT FOR SPEECH RECOGNITION
  26. AUDIO CONCEPT CLASSIFICATION WITH HIERARCHICAL DEEP NEURAL NETWORKS
  27. Noise-Robust Speech Recognition Using Deep Neural Network
  28. Acceleration Strategies for Speech Recognition Based on Deep Neural Networks
  29. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training
  30. Deep convolutional neural networks for large-scale speech tasks
  31. A Deep Learning Approach to Data-driven Parameterizations for Statistical Parametric Speech Synthesis
  32. Improving Acoustic Model for Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Bottleneck Features
  33. The relation of eye gaze and face pose: Potential impact on speech recognition
  34. Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments
  35. Binaural Classification for Reverberant Speech Segregation Using Deep Neural Networks
  36. Computational modeling and validation of the motor contribution to speech perception
  37. Deep Neural Networks For Spoken Dialog Systems
  38. Neural Network Based Pitch Tracking In Very Noisy Speech
  39. An Investigation of Implementation and Performance Analysis of Dnn Based Speech Synthesis System
  40. Ensemble Learning Approaches in Speech Recognition
  41. Raw Speech Signal-based Continuous Speech Recognition using Convolutional Neural Networks
  42. Feature Mapping of Multiple Beamformed Sources for Robust Overlapping Speech Recognition Using a Microphone Array
  43. Dysarthric Speech Recognition Using a Convolutive Bottleneck Network
  44. Cross-language speech attribute detection and phone recognition for Tibetan using deep learning
  45. Mapping between ultrasound and vowel speech using Dnn framework
  46. Improving generation performance of speech emotion recognition by denoising autoencoders
  47. Research on deep neural network’s hidden layers in phoneme recognition
  48. Cross-language transfer learning for deep neural network based speech enhancement
  49. Performance evaluation of deep bottleneck features for spoken language identification
  50. Multiple time-span feature fusion for deep neural network modeling
  51. Investigation of stochastic Hessian-Free optimization in Deep neural networks for speech recognition
  52. Phonotactic language recognition based on Dnn-hmm acoustic model
  53. Labeling unsegmented sequence data with Dnn-hmm and its application for speech recognition
  54. Building an ensemble of Cd-dnn-hmm acoustic model using random forests of phonetic decision trees
  55. Speaker adaptation of hybrid Nn/hmm model for speech recognition based on singular value decomposition
  56. Decision tree based state tying for speech recognition using Dnn derived embeddings
  57. Deep belief network based Crf for spoken language understanding
  58. A fusion approach to spoken language identification based on combining multiple phone recognizers and speech attribute detectors
  59. Patch-Based Models of Spectrogram Edges for Phone Classification
  60. Cross-Dialectal Voice Conversion with Neural Networks
  61. Trope
  62. Non-negative Factor Analysis of Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition
  63. Speech Emotion Recognition Using Cnn
  64. Joint Phoneme Segmentation Inference and Classification using CRFs
  65. Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding
  66. Supervised Speech Separation And Processing
  67. Deep Neural Network Based Speech Separation for Robust Speech Recognition
  68. Speech Separation of A Target Speaker Based on Deep Neural Networks
  69. Extracting Deep Bottleneck Features For Visual Speech Recognition
  70. A critical examination of deep learning approaches to automated speech recognition
  71. End-to-end Continuous Speech Recognition using Attention-based Recurrent Nn: First Results
  72. Automatic Speech Recognition: A Deep Learning Approach
  73. Deep neural network adaptation for children’s and adults’ speech recognition
  74. Vocal Tract Length Normalisation Approaches To Dnn-based Children’s And Adults’speech Recognition
  75. Audio-visual speech recognition using deep learning
  76. DeepSpeech: Scaling up end-to-end speech recognition
  77. Learning linearly separable features for speech recognition using convolutional neural networks
  78. Speech Enhancement Based on Analysis–Synthesis Framework With Improved Pitch Estimation and Spectral Envelope Enhancement
  79. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers
  80. Soft context clustering for F0 modeling in HMM-based speech synthesis
  81. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  82. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  83. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  84. Noisy Training for Deep Neural Networks in Speech Recognition
  85. Deep Multimodal Learning for Audio-Visual Speech Recognition
  86. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  87. Robust Excitation-based Features For Automatic Speech Recognition
  88. Machine Learning in Automatic Speech Recognition: A Survey

 

Speech Synthesis

  1. Parametric Speech Synthesis Using Local and Global Sparse Gaussian
  2. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network

 

Stability

  1. On the Stability of Deep Networks

 

Statistical Inference

  1. Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels

 

Stochastic

  1. Stochastic Spectral Descent for Restricted Boltzmann Machines
  2. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM
  3. On Graduated Optimization for Stochastic Non-Convex Problems
  4. GSNs: Generative Stochastic Networks

 

Stochastic Gradient

  1. Mean-normalized stochastic gradient for large-scale deep learning
  2. MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING
  3. Improving training time of deep neural networkwith asynchronous averaged stochastic gradient descent
  4. Stochastic Descent Analysis of Representation Learning Algorithms
  5. Deep learning with Elastic Averaging Sgd
  6. Adasecant: Robust Adaptive Secant Method for Stochastic Gradient
  7. Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods

 

Stochastic Gradient Descent

  1. 1-Bit Stochastic Gradient Descent and its Application to Data-Parallel Distributed Training of Speech DNNs
  2. On Parallelizability of Stochastic Gradient Descent for Speech DNNs
  3. Exploring one pass learning for deep neural network training with averaged stochastic gradient descent
  4. Asynchronous stochastic optimization for sequence training of deep neural networks
  5. Improving training time of deep neural networkwith asynchronous averaged stochastic gradient descent

 

Stochastic Optimization

  1. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM

 

Strategiesx

  1. A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks

 

Structured Networks

  1. Fully Connected Deep Structured Networks

 

Study

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Constrained Extreme Learning Machines: A Study on Classification Cases
  3. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  4. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  5. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  6. Threshold concepts in the Scholarship of Teaching and Learning: a phenomenological study of educational leaders in a Canadian research-intensive university

 

Subspace Analysis

  1. Human Interaction Recognition Using Independent Subspace Analysis Algorithm

 

Subspace Learning

  1. Greedy Approaches to Semi-Supervised Subspace Learning

 

Summarization

  1. Video summarization based on Subclass Support Vector Data Description
  2. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization
  3. Co-Regularized Deep Representations for Video Summarization

 

Supervised

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Explicit knowledge extraction in information-theoretic supervised multi-layered Som
  3. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  4. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  5. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery
  6. Shoe: Supervised Hashing with Output Embeddings
  7. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  8. Unsupervised Deep Learning: A Short Review
  9. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  10. Unsupervised Deep Network Pretraining via Human Design
  11. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  12. Deep Transfer Network: Unsupervised Domain Adaptation
  13. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  14. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  15. Supervised descent method with low rank and sparsity constraints for robust face alignment
  16. Soft sensor development for nonlinear and time‐varying processes based on supervised ensemble learning with improved process state partition
  17. Unsupervised word sense induction using rival penalized competitive learning
  18. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  19. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
  20. Speech emotion recognition with unsupervised feature learning
  21. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

Supervised Learning

  1. Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?

 

Support Vector Machine

  1. Deep Twin Support Vector Machine
  2. Continuous Hyper-parameter Learning for Support Vector Machines
  3. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Support Vector Machines

  1. Deep learning of support vector machines with class probability output networks
  2. Continuous Hyper-parameter Learning for Support Vector Machines

 

Surrogates

  1. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates

 

Survey

  1. A tutorial survey of architectures, algorithms, and applications for deep learning
  2. A brief survey on deep belief networks and introducing a new object oriented MATLAB toolbox (DeeBNet)
  3. Neural Networks: A Review
  4. Deep Learning for Content-Based Image Retrieval: A Comprehensive Study
  5. Facial Feature Point Detection: A Comprehensive Survey
  6. Visual Domain Adaptation: A Survey of Recent Advances
  7. A Survey of Regularization Methods for Deep Neural Network
  8. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  9. Object Recognition Using Deep Neural Networks: A Survey
  10. Survey of Local Descriptor of Object Recognition System based on Rgb-d Images
  11. Non-Distortion-Specific no-reference image quality assessment: A survey
  12. Comparative Study Of Machine Learning Techniques For Supervised Classification Of Biomedical Data
  13. A survey of research on cloud robotics and automation
  14. Transfer Learning using Computational Intelligence: A Survey
  15. Machine Learning in Automatic Speech Recognition: A Survey

 

Svm

  1. How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
  2. An Innovative Svm for Wheat Seed Quality Estimation⋆
  3. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  4. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Swarm Optimization

  1. Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks
  2. The Synergistic Combination of Particle Swarm Optimization and Fuzzy Sets to Design Granular Classifier

 

Synonym Extraction

  1. Practice in Synonym Extraction at Large Scale

 

Target Coding

  1. Deep Representation Learning with Target Coding

 

Target Detection

  1. Graph-Based Supervised Automatic Target Detection

 

Temporal

  1. Accelerated gradient temporal difference learning algorithms
  2. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  3. HFirst: A Temporal Approach to Object Recognition
  4. Learning invariant object recognition from temporal correlation in a hierarchical network
  5. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  6. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  7. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  8. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  9. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  10. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism

 

Temporal Dependencies

  1. Learning Temporal Dependencies in Data Using a Dbn-blstm

 

Tensor

  1. Matrix and Tensor Features for Discriminative Learning

 

Term

  1. Accurate localized short term weather prediction for renewables planning
  2. Retrieval Term Prediction Using Deep Belief Networks
  3. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  4. Deep Sentence Embedding Using the Long Short Term Memory Network: Analysis and Application to Information Retrieval
  5. Compositional Distributional Semantics with Long Short Term Memory

 

Text Classification

  1. Deep Belief Networks and Biomedical Text Categorisation
  2. Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

 

Text Recognition

  1. Deep Structured Output Learning for Unconstrained Text Recognition

 

Texture Recognition

  1. Deep convolutional filter banks for texture recognition and segmentation

 

Theano

  1. Theano-based Large-Scale Visual Recognition with Multiple GPUs

 

Theory

  1. Adaptive Information-Theoretical Feature Selection for Pattern Classification
  2. The atoms of neural computation
  3. On The Dynamical Nature Of Computation
  4. Supplementary Material: On the Number of Linear Regions of Deep Neural Networks
  5. Why does Deep Learning work?-A perspective from Group Theory
  6. Advanced Mean Field Theory of Restricted Boltzmann Machine
  7. Brain as an Emergent Finite Automaton: A Theory and Three Theorems
  8. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  9. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  10. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  11. Multithreshold Entropy Linear Classifier: Theory and Applications

 

Thermodynamics

  1. Deep Unsupervised Learning using Nonequilibrium Thermodynamics

 

Thin Deep Networks

  1. FitNets: Hints for Thin Deep Nets

 

Time Series

  1. A review of unsupervised feature learning and deep learning for time-series modeling
  2. Learning Methods for Variable Selection and Time Series Prediction
  3. Structured Recurrent Temporal Restricted Boltzmann Machines
  4. Deep Multimodal Fusion: Combining Discrete Events and Continuous Signals
  5. Query Optimization in Heterogeneous Cpu/gpu Environment for Time Series Databases
  6. Temporal Dropout of Changes Approach to Convolutional Learning of Spatio-Temporal Features
  7. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video
  8. Dual-domain Hierarchical Classification of Phonetic Time Series
  9. Support Vector-Based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification
  10. Error Modeling Approach to Improve Time Series Forecasters

 

Tongue

  1. Testing AutoTrace: A machine-learning approach to automated tongue contour data extraction

 

Tool

  1. Introducing CURRENNT–the Munich open-source Cuda RecurREnt Neural Network Toolkit

 

Tools

  1. R for Cloud Computing

 

Topic Modelling

  1. A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data
  2. A Novel Neural Topic Model and Its Supervised Extension

 

Traffic

  1. Traffic Flow Prediction With Big Data: A Deep Learning Approach
  2. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  3. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning
  4. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  5. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  6. A novel pLSA based Traffic Signs Classification System

 

Traffic Prediction

  1. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces

 

Traffic Sign

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  2. A novel pLSA based Traffic Signs Classification System

 

Transcription

  1. Sequence transcription with deep neural networks

 

Transductive

  1. Transductive Multi-view Zero-Shot Learning

 

Transfer Learning

  1. Transfer Learning for Video Recognition with Scarce Training Data
  2. Deep Multi-Instance Transfer Learning
  3. Representation Sharing and Transfer in Deep Neural Networks
  4. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers
  5. Robust face recognition via transfer learning for robot partner
  6. Transfer Learning using Computational Intelligence: A Survey

 

Tree Structure

  1. When Are Tree Structures Necessary for Deep Learning of Representations?

 

Tree Structures

  1. When Are Tree Structures Necessary for Deep Learning of Representations?

 

Trends

  1. Foundations and Trends® in Computer Graphics and Vision

 

Twitter

  1. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data

 

Ultrasound

  1. Mapping between ultrasound and vowel speech using Dnn framework
  2. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners

 

Una

  1. UAV Application for DARPA PERFECT

 

Unsupervised

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  3. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  4. Unsupervised Deep Learning: A Short Review
  5. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  6. Unsupervised Deep Network Pretraining via Human Design
  7. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  8. Deep Transfer Network: Unsupervised Domain Adaptation
  9. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  10. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  11. Unsupervised word sense induction using rival penalized competitive learning
  12. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  13. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
  14. Speech emotion recognition with unsupervised feature learning
  15. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

Unsupervised Learning

  1. Unsupervised learning of hierarchical representations with convolutional deep belief networks
  2. Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations
  3. Deep unsupervised network for multimodal perception, representation and classification
  4. Unsupervised Deep Haar Scattering on Graphs
  5. Unsupervised Learning of Semantics of Object Detections for Scene Categorization
  6. Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web
  7. Pedestrian Detection Based on Multi-Stage Unsupervised Learning
  8. From neural Pca to deep unsupervised learning
  9. Learning Face Representation from Scratch
  10. Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering
  11. Unsupervised feature learning on monaural Doa estimation using convolutional deep belief networks
  12. Unsupervised generation of context-relevant training-sets for visual object recognition employing multilinguality
  13. Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework
  14. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition
  15. Unsupervised Domain Adaptation with Feature Embeddings
  16. Unsupervised Learning of Spatiotemporally Coherent Metrics
  17. An Analysis of Unsupervised Pre-training in Light of Recent Advances
  18. C-SVDDNet: An Effective Single-Layer Network for Unsupervised Feature Learning
  19. Fingerprint Enhancement Using Unsupervised Hierarchical Feature Learning
  20. Unsupervised Feature Learning for Dense Correspondences across Scenes

 

User Authentication

  1. Keystroke Dynamics User Authentication Using Advanced Machine Learning Methods

 

User Interface

  1. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

User Interfaces

  1. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Vehicle

  1. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  2. Vehicle Detection in Aerial Imagery: A small target detection benchmark

 

Vehicle Classification

  1. Vehicle Type Classification Using Unsupervised Convolutional Neural Network

 

Vehicle Classificationx

  1. Vehicle Type Classification Using Semi-Supervised Convolutional Neural Network

 

Vehicle Recognition

  1. Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks

 

Video

  1. Challenge Huawei challenge: Fusing multimodal features with deep neural networks for Mobile Video Annotation
  2. Reducing structure of deep Convolutional Neural Networks for Huawei Accurate and Fast Mobile Video Annotation Challenge
  3. Modeling Video Dynamics with Deep Dynencoder
  4. Large-scale video classification with convolutional neural networks
  5. Machine Learning in Intelligent Video and Automated Monitoring
  6. Transfer Learning for Video Recognition with Scarce Training Data
  7. Effects on learning of multimedia animation combined with multidimensional concept maps
  8. MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
  9. A Study of Feature Combination in Gesture Recognition with Kinect
  10. Video Event Detection via Multi-modality Deep Learning
  11. Semantic parsing for priming object detection in indoors Rgb-d scenes
  12. Fusing Music and Video Modalities Using Multi-timescale Shared Representations
  13. Mask Assisted Object Coding with Deep Learning for Object Retrieval in Surveillance Videos
  14. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video
  15. Automatic face annotation in Tv series by video/script alignment
  16. Building a Post-Compression Region-of-Interest Encryption Framework for Existing Video Surveillance Systems
  17. Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web
  18. C3d: Generic Features for Video Analysis
  19. Video Event Detection via Multi-modality Deep Learning
  20. Audio-based annnotatoion of video
  21. Translating Videos to Natural Language Using Deep Recurrent Neural Networks
  22. Learning features and their transformations from natural videos
  23. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  24. Video summarization based on Subclass Support Vector Data Description
  25. Co-Regularized Deep Representations for Video Summarization
  26. Dense 3d Face Alignment from 2d Videos in Real-Time
  27. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  28. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  29. Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research
  30. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  31. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  32. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Videos

  1. Learning features and their transformations from natural videos
  2. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  3. Dense 3d Face Alignment from 2d Videos in Real-Time
  4. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  5. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Vision

  1. Towards an Embodied Developing Vision System

 

Visual

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  3. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  4. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments
  5. Deep Multimodal Learning for Audio-Visual Speech Recognition
  6. Two Dimensional Hashing for Visual Tracking
  7. A Hmax with Llc for visual recognition
  8. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
  9. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  10. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  11. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  12. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  13. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  14. Domain Adaptation for Visual Recognition
  15. Learning Discriminative Feature Representations for Visual Categorization
  16. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data
  17. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Visual Memory

  1. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments

 

Vocal

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  2. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks

 

Voice Recognition

  1. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training

 

Vowel

  1. Exploration of Deep Belief Networks for Vowel-like regions detection

 

Weather Prediction

  1. Accurate localized short term weather prediction for renewables planning

 

Web Mining

  1. A Method For Extracting Information From The Web Using Deep Learning Algorithm

 

Web Search

  1. Deep Learning for Web Search and Natural Language Processing

 

Web Spam

  1. Comparisons of machine learning techniques for detecting malicious webpages

 

Weed Classification

  1. Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a Uav

 

Weld

  1. Application of Deep Neural Network in Estimation of the Weld Bead Parameters

 

Wind Power

  1. Wind Power Prediction and Pattern Feature Based on Deep Learning Method

 

Word Embeddings

  1. Deep Multilingual Correlation for Improved Word Embeddings

 

Word Segmentation

  1. Learning Character Representations for Chinese Word Segmentation

 

Word Sense

  1. Unsupervised word sense induction using rival penalized competitive learning

 

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@misc{2014DPalazRCollobert,
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@misc{2014DQuangYChenXXie,
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@misc{2014DRasmussen,
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@misc{2014DSovilj,
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@misc{2014DStowellMDPlumbley,
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@misc{2014DTranLBourdevRFergusLTorresaniMPaluri,
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@misc{2014DTristramKBradshaw,
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@misc{2014DTurcsanyABargiela,
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@misc{2014DVRao,
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@misc{2014DWangXTan,
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@misc{2014DWardeFarleyARabinovichDAnguelov,
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@misc{2014DWuLShao,
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@misc{2014DXWuWPanLDXieCXHuang,
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@misc{2014DYAmit,
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@misc{2014DYiZLeiSLiaoSZLi,
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@misc{2014DYiZLeiSZLi,
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@misc{2014DYuLDeng,
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@misc{2014DYuLDengAutomaticSpeechRecognition:,
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@misc{2014DYuLDengDeepNeuralNetwork-Hidden,
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@misc{2014DYuLDengDeepNeuralNetworks,
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@misc{2014DYuLDengFeatureRepresentationLearning,
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@misc{2014DYuLDengHiddenMarkovModels,
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@misc{2014DYuLDengRepresentationSharingand,
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@misc{2014EBATI,
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@misc{2014EBarshanPFieguth,
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@misc{2014EBengioYWenSRuan,
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@misc{2014ECakir,
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@misc{2014ECovielloGLanckriet,
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@misc{2014EHofferNAilon,
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@misc{2014EMRehnHSprekeler,
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@misc{2014EOyallonSMallat,
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@misc{2014EPanZHan,
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@misc{2014ETzengJHoffmanNZhangKSaenkoTDarrell,
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@misc{2014FAgostinelliMHoffmanPSadowskiPBaldi,
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@misc{2014FBarrancoCFermullerYAloimonos,
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@misc{2014FFengRLiXWang,
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@misc{2014FFengXWangRLi,
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@misc{2014FLiuCShenGLin,
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@misc{2014FSrajerAGSchwingMPollefeysTPajdla,
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@misc{2014FWeningerJBergmannBSchuller,
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@misc{2014FZouYWangYYangKZhouYChenJSong,
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@misc{2014GAOWeixunCAOQiyingQYao,
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@misc{2014GAttardiVCozzaDSartiano,
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@misc{2014GBRhoads,
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@misc{2014GChen,
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@misc{2014GChenSNSrihari,
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@misc{2014GDesjardinsHLuoACourvilleYBengio,
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@misc{2014GEvangelidisGSinghRHoraud,
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@misc{2014GLayherFSchrodtMVButzHNeumann,
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@misc{2014GMarcusAMarblestoneTDean,
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@misc{2014GMesnilYDauphinKYaoYBengioLDeng,
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@misc{2014GMishneRTalmonICohen,
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@misc{2014GMontufar,
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@misc{2014GMontúfarRPascanuKChoYBengio,
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@misc{2014GPapandreouIKokkinosPASavalle,
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@misc{2014GRieglerDFerstlMRütherHBischof,
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@misc{2014GVHahnPowellDArchangeli,
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@misc{2014GZhongMCheriet,
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@misc{2014HAjakanPGermainHLarochelleFLaviolette,
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@misc{2014HBKazemianSAhmed,
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@misc{2014HChoiHPark,
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@misc{2014HFGolinoCMAGomesDAndrade,
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@misc{2014HFanMYangZCaoYJiangQYin,
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@misc{2014HFangCHu,
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@misc{2014HHamooniAMueen,
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@misc{2014HLiuBMaLQinJPangCZhangQHuang,
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@misc{2014HLvGYuXTianGWu,
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@misc{2014HMobahiJWFisherIII,
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@misc{2014HMobahiJWFisherIIICoarse-to-FineMinimizationof,
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@misc{2014HPMartínezGNYannakakis,
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@misc{2014HPanSIOlsenYZhu,
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@misc{2014HQiaoXXiYLiWWuFLi,
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@misc{2014HQuXXieYLiuMZhangLLu,
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@misc{2014HSchulzKChoTRaikoSBehnke,
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@misc{2014HSu,
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@misc{2014HTYuFRen,
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@misc{2014HTosun,
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@misc{2014HVKoops,
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@misc{2014HValpola,
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@misc{2014HWang,
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@misc{2014HWangClassifyingGray-scaleSar,
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@misc{2014HWangNWangDYYeung,
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@misc{2014HWangXShiDYYeung,
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@misc{2014HWangYZhaoYXuXXuXSuoQJi,
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@misc{2014HYanJLuXZhou,
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@misc{2014HYangIPatras,
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@misc{2014HYinXJiaoYChaiBFang,
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@misc{2014HZhaoPPoupartYZhangMLysy,
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@misc{2014HZhouGBHuangZLinHWangYCSoh,
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@misc{2014HZhouJTangHZheng,
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@misc{2014ICortesCirianoQulAinVSubramanianBLenselink,
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@misc{2014IHJhuoDTLee,
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@misc{2014IJGoodfellowJPougetAbadieMMirzaBXu,
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@misc{2014IJKimXXie,
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@misc{2014INwoguYZhou,
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@misc{2014ISutskeverOVinyalsQVLe,
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@misc{2014ITitovEKhoddam,
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@misc{2014ITseyzer,
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@misc{2014JAVanegasJArevaloSOtáloraFPáez,
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@misc{2014JBergstraBKomerCEliasmithDWardeFarley,
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@misc{2014JBohannon,
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@misc{2014JCBanCHChang,
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@misc{2014JCarreiraAKarSTulsianiJMalik,
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@misc{2014JChorowskiDBahdanauKChoYBengio,
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@misc{2014JChungCGulcehreKHChoYBengio,
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@misc{2014JCummer,
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@misc{2014JDaiYNWu,
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@misc{2014JDonahueLAHendricksSGuadarramaMRohrbach,
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@misc{2014JDongSSoatto,
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@misc{2014JDu,
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@misc{2014JEdwards,
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@misc{2014JGADolfingKMGroetheRSDixonJRBellegarda,
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@misc{2014JGDolfingJRBellegardaUMeierRDixon,
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@misc{2014JGlass,
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@misc{2014JHelmsen,
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@misc{2014JHuangWXiaSYan,
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@misc{2014JJiangRHuLMikelYDou,
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@misc{2014JKChenZChenZChiHFu,
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@misc{2014JLedererSGuadarrama,
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@misc{2014JLehmanJCluneSRisi,
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@misc{2014JLi,
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@misc{2014JLiHChangJYang,
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@misc{2014JLiZStruzikLZhangACichocki,
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@misc{2014JLiuMGongJZhaoHLiLJiao,
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@misc{2014JLongEShelhamerTDarrell,
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@misc{2014JLyonsADehzangiRHeffernanASharma,
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@misc{2014JMBae,
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@misc{2014JMTomczakMZięba,
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@misc{2014JMacákODrbohlav,
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@misc{2014JMairalFBachJPonce,
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@misc{2014JMaoWXuYYangJWangALYuille,
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@misc{2014JMartinezHHHoosJJLittle,
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@misc{2014JNiuYQianKYu,
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@misc{2014JRSmith,
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@misc{2014JRedmonAAngelova,
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@misc{2014JRudyWDingDJImGWTaylor,
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@misc{2014JShenMLee,
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@misc{2014JTHLoYGuiYPeng,
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@misc{2014JWanDWangSCHHoiPWuJZhuYZhangJLi,
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@misc{2014JWangCKangYHeSXiangCPan,
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@misc{2014JWangZDengSWangQGao,
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@misc{2014JXuHLiSZhou,
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@misc{2014JYYu,
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@misc{2014JYangYSunLZhangQZhang,
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@misc{2014JYosinskiJCluneYBengioHLipson,
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@misc{2014JZhangMKanSShanXZhaoXChen,
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@misc{2014KAddankiDWu,
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@misc{2014KBISWARANJANSSARKARDRASETHI,
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@misc{2014KBRajaRRaghavendraVKVemuriCBusch,
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@misc{2014KChalupkaPPeronaFEberhardt,
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@misc{2014KChangCChen,
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@misc{2014KDuh,
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@misc{2014KEggenspergerFHutterHHHoosKLeytonBrown,
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@misc{2014KFragkiadakiPArbelaezPFelsenJMalik,
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@misc{2014KGoelRVohra,
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@misc{2014KHan,
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@misc{2014KHanDWang,
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@misc{2014KHeJSun,
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@misc{2014KHwangWSung,
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@misc{2014KINTEKNG,
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@misc{2014KKangXWang,
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@misc{2014KKim,
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@misc{2014KLencAVedaldi,
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@misc{2014KRohanimanesh,
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@misc{2014KSTaiSXu,
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@misc{2014KTengJWangMXuHLu,
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@misc{2014LAvdiyenkoNBertschingerJJost,
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@misc{2014LCChenGPapandreouIKokkinosKMurphy,
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@misc{2014LCaoCWang,
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@misc{2014LChaoJTaoMYangYLiZWen,
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@misc{2014LChenSZhuZLiJHu,
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@misc{2014LDengXHeGTurDHakkanitur,
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@misc{2014LDenoyerPGallinari,
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@misc{2014LDinhDKruegerYBengio,
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@misc{2014LGHafemann,
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@misc{2014LGuoSLiXNiuYDou,
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@misc{2014LHChenZHLingLJLiuLRDai,
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@misc{2014LLMaJWu,
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@misc{2014LLiuJHuSZhangWDeng,
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@misc{2014LNieSZKumar,
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@misc{2014LShenGSunSWangEWuQHuang,
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@misc{2014LYuKMHermannPBlunsomSPulman,
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@misc{2014LZhangYFNieZHWang,
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@misc{2014LZhaoKJia,
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@misc{2014MAKeyvanradMMHomayounpour,
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@misc{2014MBlaschko,
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@misc{2014MCimpoiSMajiAVedaldi,
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@misc{2014MCourbariauxYBengioJPDavid,
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@misc{2014MDCollinsPKohli,
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@misc{2014MDMcDonnellMDTisseraAvanSchaikJTapson,
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@misc{2014MEMidhunSRNairVTPrabhakarSSKumar,
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@misc{2014MGhifaryWBKleijnMZhang,
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@misc{2014MHarandiMSalzmann,
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@misc{2014MJSkwarkDRaimondiMMichelAElofsson,
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@misc{2014MJWitteveen,
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@misc{2014MJanzaminHSedghiAAnandkumar,
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@misc{2014MJanzaminHSedghiAAnandkumarScoreFunctionFeatures,
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@misc{2014MJungJHwangJTani,
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@misc{2014MKarthickSUmesh,
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@misc{2014MKhalilHaniLSSung,
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@misc{2014MKiefelVJampaniPVGehler,
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@misc{2014MKim,
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@misc{2014MKlećDKoržinek,
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@misc{2014MKorpusikNSchmidtJDrexlerSCyphersJGlass,
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@misc{2014MKoutsombogeraHPapageorgiou,
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@misc{2014MLeordeanuARaduRSukthankar,
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@misc{2014MLiDGAndersenJWParkAJSmolaAAhmed,
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@misc{2014MLiangZLiTChenJZeng,
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@misc{2014MLinSLiXLuoSYan,
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@misc{2014MLängkvistALoutfi,
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@misc{2014MMalinowskiMFritz,
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@misc{2014MMirzaSOsindero,
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@misc{2014MPesekALeonardisMMarolt,
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@misc{2014MRFerrier,
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@misc{2014MRavanelliVHDoAJanin,
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@misc{2014MSahasrabudheAMNamboodiri,
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@misc{2014MSchikoraASchikora,
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@misc{2014MSchuldISinayskiyFPetruccione,
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@misc{2014MSongTChambers,
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@misc{2014MStoehrYAmit,
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@misc{2014MTanakaMOkutomi,
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@misc{2014MThulinPMasek,
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@misc{2014MUedaYNishitaniYKanekoAOmote,
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@misc{2014MUngerLRokachABarEGudesBShapira,
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@misc{2014MWangYChenXWang,
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@misc{2014MZengLTNguyenBYuOJMengshoelJZhuPWu,
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@misc{2014MZhaoCZhuangYWangTSLee,
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@misc{2014NCohenAShashua,
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@misc{2014NItenDPetko,
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@misc{2014RMKeller,
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@misc{2014SZhangFQiaoMLiu,
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@misc{2014SZhangKKang,
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@misc{2014SZhaoHYaoSZhaoXJiangXJiang,
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@misc{2014SZhouQChenXWang,
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@misc{2015JBaiYWuJZhangFChen,
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@misc{2015JBrunaSChintalaYLeCunSPiantinoASzlam,
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@misc{2015JDaiKHeJSun,
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@misc{2015JEslavaRios,
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@misc{2015JGaoXHeLDeng,
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@misc{2015JGauthier,
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@misc{2015JGirardMREmami,
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@misc{2015JHanDZhangSWenLGuoTLiuXLi,
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@misc{2015JHeaton,
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@misc{2015JHosangMOmranRBenensonBSchiele,
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@misc{2015JIbarzYBulatovIGoodfellow,
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@misc{2015JJohnsonZJiangMYanez,
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@misc{2015JKDuttaBBanerjee,
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@misc{2015JKONGKSUNMJIANGHHUOAYIMING,
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@misc{2015JKarhunenTRaikoKHCho,
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@misc{2015JKuenKMLimCPLee,
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@misc{2015JLiDJurafskyEHovy,
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@misc{2015JLiangKKelly,
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@misc{2015JLinOMorereVChandrasekharAVeillardHGoh,
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@misc{2015JLiuKZhaoBKusyJWenRJurdak,
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@misc{2015JLuVBehboodPHaoHZuoSXueGZhang,
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@misc{2015JLuVELiongXZhouJZhou,
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@misc{2015JMaRPSheridanALiawGDahlVSvetnik,
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@misc{2015JMansanetAAlbiolRParedesAAlbiol,
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@misc{2015JMartensRGrosse,
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@misc{2015JPadmanabhanMJJohnsonPremkumar,
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@misc{2015JSnoekORippelKSwerskyRKirosNSatish,
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@misc{2015JSohlDicksteinEAWeissNMaheswaranathan,
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@misc{2015JSunWCaoZXuJPonce,
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@misc{2015JTayyubATavanaiYGatsoulisAGCohnDCHogg,
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@misc{2015JWHaKMKimBTZhang,
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@misc{2015JWeng,
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@misc{2015JYoungNHawes,
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@misc{2015JZhangSNguyenYShangDXuIKosztin,
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@misc{2015JvandeWeijerFSKhan,
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@misc{2015KGregorIDanihelkaAGravesDWierstra,
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@misc{2015KHLauYHTayFLLo,
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@misc{2015KHeXZhangSRenJSun,
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@misc{2015KLiGQiJYeKAHua,
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@misc{2015KMiuraTHarada,
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@misc{2015KNiRPearceKBoakyeBVanEssenDBorth,
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@misc{2015KSelyuninDRatasichEBartocciRGrosu,
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@misc{2015KXuJBaRKirosACourvilleRSalakhutdinov,
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@misc{2015LAJeniJFCohnTKanade,
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@misc{2015LEBeerKRodriguezCTaylorNMartinezJones,
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@misc{2015LJDengWGuoTZHuang,
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@misc{2015LLWangNHCYung,
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@misc{2015LLiu,
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@misc{2015LLiuLShaoXLiKLu,
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@misc{2015LMcAfeeKOlukotun,
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@misc{2015LPigouSDielemanPJKindermansBSchrauwen,
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@misc{2015LYaoATorabiKChoNBallasCPalHLarochelle,
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@misc{2015LZhangLLinXWuSDingLZhang,
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@misc{2015LZhengKIdrissiCGarciaSDuffnerABaskurt,
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@misc{2015MAlber,
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@misc{2015MAslanASengurYXiaoHWangMCInceXMa,
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@misc{2015MBackstromDCOOPER,
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@misc{2015MCicconetDGeigerMWerman,
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@misc{2015MDobrotaMVujošević,
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@misc{2015MGermainKGregorIMurrayHLarochelle,
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@misc{2015MGheisariMSBaghshah,
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@misc{2015MHaloi,
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@misc{2015MHermansMSorianoJDambrePBienstman,
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@misc{2015MHirnNPoilvertSMallat,
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@misc{2015MKharratzadehTRShultz,
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@misc{2015MKimLRigazio,
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@misc{2015MLessmannRPWürtz,
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@misc{2015MMNajafabadiFVillanustreTMKhoshgoftaar,
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@misc{2015MMSaleem,
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@misc{2015MNStolarMLechISBurnett,
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@misc{2015MOYahaya,
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@misc{2015MOberwegerPWohlhartVLepetit,
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@misc{2015MOhzeki,
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@misc{2015MOhzekiL_1-regularizedBoltzmannmachine,
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@misc{2015MPeemenBMesmanHCorporaal,
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@misc{2015MPeemenBMesmanHCorporaalInter-TileReuseOptimization,
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@misc{2015MProbst,
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@misc{2015MSGashlerZKindle,
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@misc{2015MSahasrabudhe,
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@misc{2015MSongZSunKLiuXLang,
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@misc{2015MThom,
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@misc{2015MUzairFShafaitBGhanemAMian,
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@misc{2015MWangZLuHLiQLiu,
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@misc{2015MWeinmannBJutziSHinzCMallet,
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@misc{2015MYLiuAMallyaOCTuzelXChen,
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@misc{2015MYasuda,
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@misc{2015MZhou,
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@misc{2015NJieBXiongzhuLZhongWYao,
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@misc{2015NJojicAPerinaDKim,
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@misc{2015NKarnaISuwardiNMaulidevi,
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@misc{2015NNguyenAYoshitaka,
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@misc{2015NTishbyNZaslavsky,
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@misc{2015NWangSLiAGuptaDYYeung,
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@misc{2015NYHammerlaJMFisherPAndrasLRochester,
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@misc{2015OLemonAEshghi,
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@misc{2015PAgarwalAKumar,
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@misc{2015PBaldiPSadowskiDWhiteson,
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@misc{2015PKuhadAYassineSShirmohammadi,
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@misc{2015PLeWZuidema,
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@misc{2015PSSattigeri,
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@misc{2015PSinghAVermaNSChaudhari,
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@misc{2015PVerbancsicsJHarguess,
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@misc{2015PWohlhartVLepetit,
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@misc{2015QBNguyenTTVuCMLuong,
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@misc{2015QLvYDouXNiuJXuJXuFXia,
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@misc{2015QMaITanigawaMMurata,
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@misc{2015QWangJFangYYuan,
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@misc{2015RAManapLShao,
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@misc{2015RBahgat,
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@misc{2015RBruecknerBSchuller,
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@misc{2015RFuJGuoBQinWCheHWangTLiu,
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@misc{2015RGopalanRLiVMPatelRChellappa,
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@misc{2015RKSarvadevabhatlaRVBabu,
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@misc{2015RKamimura,
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@misc{2015RMCCOPPIN,
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@misc{2015RSkynerJMcDonaghCRGroomTvanMourik,
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@misc{2015RWuSYanYShanQDangGSun,
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@misc{2015SAnandaYogendran,
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@misc{2015SAroraEWMayrNOllinger,
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@misc{2015SAryalRGutierrezOsuna,
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@misc{2015SDielemanKWWillettJDambre,
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@misc{2015SFenwick,
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@misc{2015SGMatthews,
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@misc{2015SGaoLDuanITsang,
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  year = {2014}
}


@article{baldi2014searching,
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  year = {2014},
  publisher = {Nature Publishing Group}
}


@article{baucom2014survey,
  title = {Survey and Implementation of Computer Vision Techniques for Humanoid Robots},
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  year = {2014}
}


@article{bengio2014towards,
  title = {Towards Real-Time Image Understanding with Convolutional Networks},
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@inproceedings{besaw2014deep,
  title = {Deep learning algorithms for detecting explosive hazards in ground penetrating radar data},
  author = {Besaw, Lance E and Stimac, Philip J},
  booktitle = {SPIE Defense+ Security},
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  year = {2014},
  organization = {International Society for Optics and Photonics}
}


@phdthesis{bhutani2014alternate,
  title = {Alternate Layer Sparsity and Intermediate Fine-tuning for Deep Autoencoders},
  author = {Bhutani, Ankit},
  year = {2014},
  school = {INDIAN INSTITUTE OF TECHNOLOGY, KANPUR}
}


@inproceedings{bian2014reducing,
  title = {Reducing structure of deep Convolutional Neural Networks for Huawei Accurate and Fast Mobile Video Annotation Challenge},
  author = {Bian, Yunlong and Dong, Yuan and Bai, Hongliang and Liu, Bo and Wang, Kai and Liu, Yinan},
  booktitle = {Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on},
  pages = {1--6},
  year = {2014},
  organization = {IEEE}
}


@article{biem2014neural,
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  pages = {205},
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}


@article{bordes2014semantic,
  title = {A semantic matching energy function for learning with multi-relational data},
  author = {Bordes, Antoine and Glorot, Xavier and Weston, Jason and Bengio, Yoshua},
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  number = {2},
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  year = {2014},
  publisher = {Springer}
}


@article{bornschein2014reweighted,
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  author = {Bornschein, J{\"o}rg and Bengio, Yoshua},
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@article{bottou2014machine,
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@article{bruckner2014ml,
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}


@article{bumulti,
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@article{campbell2014using,
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  year = {2014}
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@article{canny2014interactive,
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@article{chatfield2014return,
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@article{chenbig,
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@article{cheng2014language,
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@article{chenvoice,
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@article{chernodub2014training,
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@article{cho2014exponentially,
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  year = {2014}
}


@article{cho2014learning,
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  year = {2014}
}


@incollection{chu2014analysis,
  title = {Analysis of Feature Maps Selection in Supervised Learning Using Convolutional Neural Networks},
  author = {Chu, Joseph Lin and Krzy{\.z}ak, Adam},
  booktitle = {Advances in Artificial Intelligence},
  pages = {59--70},
  year = {2014},
  publisher = {Springer}
}


@phdthesis{chu2014using,
  title = {Using Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks for Partially Occluded Object Recognition},
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  year = {2014},
  school = {Concordia University}
}


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@inproceedings{conti2014brain,
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  year = {2014}
}


@incollection{cui2014deep,
  title = {Deep Network Cascade for Image Super-resolution},
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  booktitle = {Computer Vision--ECCV 2014},
  pages = {49--64},
  year = {2014},
  publisher = {Springer}
}


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@inproceedings{cvpr2013aug,
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  pages = {2019--2026},
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}


@inproceedings{cvpr2013bbprbm,
  title = {Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines},
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@article{dahl2014multi,
  title = {Multi-task Neural Networks for QSAR Predictions},
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  year = {2014}
}


@article{dasigimodeling,
  title = {Modeling Newswire Events using Neural Networks for Anomaly Detection},
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@article{dauphin2014identifying,
  title = {Identifying and attacking the saddle point problem in high-dimensional non-convex optimization},
  author = {Dauphin, Yann and Pascanu, Razvan and Gulcehre, Caglar and Cho, Kyunghyun and Ganguli, Surya and Bengio, Yoshua},
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  year = {2014}
}


@article{debest,
  title = {Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images},
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@article{dedeep,
  title = {Deep learning: Modeling high-level face features through deep networks},
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}


@article{deng2014tutorial,
  title = {A tutorial survey of architectures, algorithms, and applications for deep learning},
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  pages = {e2},
  year = {2014},
  publisher = {Cambridge Univ Press}
}


@article{dengdeep,
  title = {DEEP LEARNING},
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@article{denton2014exploiting,
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  year = {2014}
}


@article{derfeature,
  title = {Feature Selection and Learning for Semantic Segmentation},
  author = {DER TECHNISCHEN, UNIVERSIT AT MUNCHEN}
}


@article{ding2014mental,
  title = {Mental Rotation by Optimizing Transforming Distance},
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  year = {2014}
}


@inproceedings{dong2014adaptive,
  title = {Adaptive multi-compositionality for recursive neural models with applications to sentiment analysis},
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  year = {2014}
}


@inproceedings{dong2014adarnn,
  title = {Adaptive recursive neural network for target-dependent twitter sentiment classification},
  author = {Dong, Li and Wei, Furu and Tan, Chuanqi and Tang, Duyu and Zhou, Ming and Xu, Ke},
  booktitle = {Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL)},
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  year = {2014}
}


@incollection{dong2014learning,
  title = {Learning a deep convolutional network for image super-resolution},
  author = {Dong, Chao and Loy, Chen Change and He, Kaiming and Tang, Xiaoou},
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  pages = {184--199},
  year = {2014},
  publisher = {Springer}
}


@article{dong2014rankcnn,
  title = {RankCNN: When learning to rank encounters the pseudo preference feedback},
  author = {Dong, Yuan and Huang, Chong and Liu, Wei},
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  number = {3},
  pages = {554--562},
  year = {2014},
  publisher = {Elsevier}
}


@inproceedings{dos2014deep,
  title = {Deep convolutional neural networks for sentiment analysis of short texts},
  author = {dos Santos, C{\i}cero Nogueira and Gatti, Ma{\i}ra},
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  year = {2014}
}


@article{dos2014think,
  title = {Think Positive: Towards Twitter Sentiment Analysis from Scratch},
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  year = {2014}
}


@incollection{evans2014machines,
  title = {Machines Learning-Towards a New Synthetic Autobiographical Memory},
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}


@article{foxtowards,
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@article{fuentes2014detection,
  title = {Detection of retransmissions in 10G Ethernet using GPUs},
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}


@article{gangireddy2014feed,
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@article{ganin2014n,
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}


@inproceedings{gao2014modeling,
  title = {Modeling interestingness with deep neural networks},
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  year = {2014}
}


@article{geras2014scheduled,
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@inproceedings{gokhale2014240,
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}


@article{goodfellow2014generative,
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  year = {2014}
}


@phdthesis{gravelines2014deep,
  title = {DEEP LEARNING VIA STACKED SPARSE AUTOENCODERS FOR AUTOMATED VOXEL-WISE BRAIN PARCELLATION BASED ON FUNCTIONAL CONNECTIVITY (Thesis format: Monograph)},
  author = {Gravelines, C{\'e}line},
  year = {2014},
  school = {The University of Western Ontario}
}


@inproceedings{gu2014implementation,
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  pages = {12},
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  organization = {ACM}
}


@incollection{gulcehre2014learned,
  title = {Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks},
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  booktitle = {Machine Learning and Knowledge Discovery in Databases},
  pages = {530--546},
  year = {2014},
  publisher = {Springer}
}


@article{gunawan2014deep,
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}


@incollection{gupta2014learning,
  title = {Learning Rich Features from RGB-D Images for Object Detection and Segmentation},
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  publisher = {Springer}
}


@article{gupta2014query,
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  year = {2014}
}


@phdthesis{han2014feature,
  title = {FEATURE GENERATION FOR QUANTIFICATION OF VISUAL SIMILARITY},
  author = {Han, Tianning Steven},
  year = {2014},
  school = {Rensselaer Polytechnic Institute}
}


@article{han2014object,
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  author = {Han, Sunhyoung and Vasconcelos, Nuno},
  journal = {Frontiers in Computational Neuroscience},
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  publisher = {Frontiers}
}


@article{hannagan2014deep,
  title = {Deep Learning of Orthographic Representations in Baboons},
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  number = {1},
  pages = {e84843},
  year = {2014},
  publisher = {Public Library of Science}
}


@phdthesis{hartmann2014friedrich,
  title = {Discriminative Convolutional Sum-Product Networks on GPU},
  author = {Hartmann, Tobias},
  year = {2014},
  school = {Rheinische Friedrich-Wilhelms-Universit{"a}t Bonn}
}


@article{he2014deep,
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  year = {2014}
}


@inproceedings{heigold2014asynchronous,
  title = {Asynchronous stochastic optimization for sequence training of deep neural networks},
  author = {Heigold, Georg and McDermott, Erik and Vanhoucke, Vincent and Senior, Andrew and Bacchiani, Michiel},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {5587--5591},
  year = {2014},
  organization = {IEEE}
}


@article{hjelm2014restricted,
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  journal = {NeuroImage},
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  pages = {245--260},
  year = {2014},
  publisher = {Elsevier}
}


@article{hoftfast,
  title = {Fast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks},
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@inproceedings{hua2014mining,
  title = {Mining knowledge from clicks: MSR-Bing image retrieval challenge},
  author = {Hua, Xian-Sheng and Ye, Ming and Li, Jin},
  booktitle = {Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on},
  pages = {1--4},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{huang2014deep,
  title = {Deep process neural network for temporal deep learning},
  author = {Huang, Wenhao and Hong, Haikun and Song, Guojie and Xie, Kunqing},
  booktitle = {Neural Networks (IJCNN), 2014 International Joint Conference on},
  pages = {465--472},
  year = {2014},
  organization = {IEEE}
}


@article{huang2014historical,
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  author = {Huang, Xuedong and Baker, James and Reddy, Raj},
  journal = {Communications of the ACM},
  volume = {57},
  number = {1},
  pages = {94--103},
  year = {2014},
  publisher = {ACM}
}


@inproceedings{huang2014kernel,
  title = {Kernel methods match deep neural networks on timit},
  author = {Huang, Po-Sen and Avron, Haim and Sainath, Tara N and Sindhwani, Vikas and Ramabhadran, Bhuvana},
  booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
  volume = {1},
  pages = {6},
  year = {2014}
}


@article{huangdeep,
  title = {Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning},
  author = {Huang, Wenhao and Song, Guojie and Hong, Haikun and Xie, Kunqing},
  publisher = {IEEE}
}


@article{iandola2014densenet,
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  journal = {arXiv preprint arXiv:1404.1869},
  year = {2014}
}


@inproceedings{icml2013pgbm,
  title = {Learning and Selecting Features Jointly with Point-wise Gated {Boltzmann} Machines},
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}


@inproceedings{icml2014srtrbm,
  title = {Structured Recurrent Temporal Restricted Boltzmann Machines},
  author = {Roni Mittelman and Benjamin Kuipers and Silvio Savarese and Honglak Lee},
  booktitle = {Proceedings of The 31st International Conference on Machine Learning},
  year = {2014}
}


@article{jaderberg2014speeding,
  title = {Speeding up Convolutional Neural Networks with Low Rank Expansions},
  author = {Jaderberg, Max and Vedaldi, Andrea and Zisserman, Andrew},
  journal = {arXiv preprint arXiv:1405.3866},
  year = {2014}
}


@article{jaderberg2014synthetic,
  title = {Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition},
  author = {Jaderberg, Max and Simonyan, Karen and Vedaldi, Andrea and Zisserman, Andrew},
  journal = {arXiv preprint arXiv:1406.2227},
  year = {2014}
}


@article{jia2014caffe,
  title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
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  year = {2014}
}


@article{jintraining,
  title = {Training Large Scale Deep Neural Networks on the Intel Xeon Phi Many-core Coprocessor},
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}


@misc{jones2014learning,
  title = {THE LEARNING MACHINES},
  author = {Jones, Nicola},
  year = {2014},
  publisher = {Nature Publishing Group MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}
}


@article{kandaswamy2014improve,
  title = {Improve Performance in Deep Neural Networks:(1) Cost Functions, and (2) Reusable learning},
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  year = {2014}
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@inproceedings{kandaswamy2014improving,
  title = {Improving Deep Neural Network Performance by Reusing Features Trained with Transductive Transference},
  author = {Kandaswamy, Chetak and Silva, Lu{\i}s and Alexandre, Lu{\i}s and Sa, J Marques and Santos, JM},
  booktitle = {Proceedings of the 24th International Conference on Artificial Neural Networks},
  year = {2014}
}


@article{kandaswamyimproving,
  title = {Improving Accuracy on Transductive Transfer Learning by Reusing SDA},
  author = {Kandaswamy, Chetak and de S{\'a}, Joaquim Marques and Silva, Lu{\'\i}s M and Alexandre, Lu{\'\i}s A and Santos, Jorge M}
}


@article{kang2014statistical,
  title = {Statistical Parametric Speech Synthesis using Weighted Multi-distribution Deep Belief Network},
  author = {Kang, Shiyin and Meng, Helen},
  year = {2014}
}


@article{kangdeep,
  title = {A DEEP LEARNING APPROACH TO DOCUMENT IMAGE QUALITY ASSESSMENT},
  author = {Kang, Le and Ye, Peng and Li, Yi and Doermann, David}
}


@article{karpathy2014deep,
  title = {Deep Fragment Embeddings for Bidirectional Image Sentence Mapping},
  author = {Karpathy, Andrej and Joulin, Armand and Fei-Fei, Li},
  journal = {arXiv preprint arXiv:1406.5679},
  year = {2014}
}


@inproceedings{karpathy2014large,
  title = {Large-scale video classification with convolutional neural networks},
  author = {Karpathy, Andrej and Toderici, George and Shetty, Sanketh and Leung, Thomas and Sukthankar, Rahul and Fei-Fei, Li},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2014}
}


@incollection{kawakami2014more,
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@incollection{li2014deep,
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@incollection{lopes2015deep,
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@inproceedings{stober2014classifying,
  title = {Classifying EEG recordings of rhythm perception},
  author = {Stober, Sebastian and Cameron, Daniel J and Grahn, Jessica A},
  booktitle = {15th International Society for Music Information Retrieval Conference (ISMIR'14)},
  year = {2014}
}


@inproceedings{stober2014does,
  title = {Does the beat go on?: identifying rhythms from brain waves recorded after their auditory presentation},
  author = {Stober, Sebastian and Cameron, Daniel J and Grahn, Jessica A},
  booktitle = {Proceedings of the 9th Audio Mostly: A Conference on Interaction With Sound},
  pages = {23},
  year = {2014},
  organization = {ACM}
}


@article{sukhbaatar2014learning,
  title = {Learning from Noisy Labels with Deep Neural Networks},
  author = {Sukhbaatar, Sainbayar and Fergus, Rob},
  journal = {arXiv preprint arXiv:1406.2080},
  year = {2014}
}


@article{sun2014deep,
  title = {Deep learning face representation by joint identification-verification},
  author = {Sun, Yi and Wang, Xiaogang and Tang, Xiaoou},
  journal = {arXiv preprint arXiv:1406.4773},
  year = {2014}
}


@inproceedings{sun2014m2c,
  title = {M2C: Energy efficient mobile cloud system for deep learning},
  author = {Sun, Kai and Chen, Zhikui and Ren, Jiankang and Yang, Song and Li, Jing},
  booktitle = {Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on},
  pages = {167--168},
  year = {2014},
  organization = {IEEE}
}


@article{sutskever2014sequence,
  title = {Sequence to Sequence Learning with Neural Networks},
  author = {Sutskever, Ilya and Vinyals, Oriol and Le, Quoc V},
  journal = {{arXiv preprint arXiv:1409.3215}, % http://arxiv.org/abs/1409.3215
year={2014}}
}


@article{taigman2014web,
  title = {Web-Scale Training for Face Identification},
  author = {Taigman, Yaniv and Yang, Ming and Ranzato, Marc'Aurelio and Wolf, Lior},
  journal = {arXiv preprint arXiv:1406.5266},
  year = {2014}
}


@article{takeda2014boundary,
  title = {Boundary Contraction Training for Acoustic Models based on Discrete Deep Neural Networks},
  author = {Takeda, Ryu and Kanda, Naoyuki and Nukaga, Nobuo},
  year = {2014}
}


@article{tang2014hierarchical,
  title = {Hierarchical kernel-based rotation and scale invariant similarity},
  author = {Tang, YY and Xia, Tian and Wei, Yantao and Li, Hong and Li, Luoqing},
  journal = {Pattern Recognition},
  volume = {47},
  number = {4},
  pages = {1674--1688},
  year = {2014},
  publisher = {Elsevier}
}


@article{terusaki2014emotion,
  title = {Emotion Detection using Deep Belief Networks},
  author = {Terusaki, Kevin and Stigliani, Vince},
  year = {2014}
}


@inproceedings{tian2014acceleration,
  title = {Acceleration Strategies for Speech Recognition Based on Deep Neural Networks},
  author = {Tian, Chao and Liu, Jia and Peng, Zhao Meng},
  booktitle = {Applied Mechanics and Materials},
  volume = {556},
  pages = {5181--5185},
  year = {2014},
  organization = {Trans Tech Publ}
}


@article{tingley2014towards,
  title = {Towards the Quantum Machine: Using Scalable Machine Learning Methods to Predict Photovoltaic Efficacy of Organic Molecules},
  author = {Tingley, Michael Alan},
  year = {2014}
}


@article{tomar2014manifold,
  title = {Manifold Regularized Deep Neural Networks},
  author = {Tomar, Vikrant Singh and Rose, Richard C},
  journal = {system},
  volume = {1},
  pages = {5},
  year = {2014}
}


@article{tompson2014joint,
  title = {Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation},
  author = {Tompson, Jonathan and Jain, Arjun and LeCun, Yann and Bregler, Christoph},
  journal = {arXiv preprint arXiv:1406.2984},
  year = {2014}
}


@article{touzetbiologically,
  title = {A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words},
  author = {Touzet, Claude and Kermorvant, Christopher and Glotin, Herv{\'e}}
}


@inproceedings{tran2014learning,
  title = {Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition},
  author = {Tran, Son N and Benetos, Emmanouil and d'Avila Garcez, Artur},
  booktitle = {Neural Networks (IJCNN), 2014 International Joint Conference on},
  pages = {2123--2129},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{tu2014challenge,
  title = {Challenge Huawei challenge: Fusing multimodal features with deep neural networks for Mobile Video Annotation},
  author = {Tu, Jian and Wu, Zuxuan and Dai, Qi and Jiang, Yu-Gang and Xue, Xiangyang},
  booktitle = {Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on},
  pages = {1--6},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{turner2014deep,
  title = {Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection},
  author = {Turner, JT and Page, Adam and Mohsenin, Tinoosh and Oates, Tim},
  booktitle = {2014 AAAI Spring Symposium Series},
  year = {2014}
}


@article{van2014analysis,
  title = {Analysis of Deep Convolutional Neural Network Architectures},
  author = {van Doorn, Joost},
  year = {2014}
}


@inproceedings{walid2014handwritten,
  title = {Handwritten digit recognition using sparse deep architectures},
  author = {Walid, Ragheb and Lasfar, Ali},
  booktitle = {Intelligent Systems: Theories and Applications (SITA-14), 2014 9th International Conference on},
  pages = {1--6},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{wang2014cascaded,
  title = {Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection},
  author = {Wang, Haibo and Cruz-Roa, Angel and Basavanhally, Ajay and Gilmore, Hannah and Shih, Natalie and Feldman, Mike and Tomaszewski, John and Gonzalez, Fabio and Madabhushi, Anant},
  booktitle = {SPIE Medical Imaging},
  pages = {90410B--90410B},
  year = {2014},
  organization = {International Society for Optics and Photonics}
}


@article{wang2014effective,
  title = {Effective Multi-Modal Retrieval based on Stacked Auto-Encoders},
  author = {Wang, Wei and Ooi, Beng Chin and Yang, Xiaoyan and Zhang, Dongxiang and Zhuang, Yueting},
  journal = {Proceedings of the VLDB Endowment},
  volume = {7},
  number = {8},
  year = {2014}
}


@inproceedings{wang2014energy,
  title = {Energy efficient neural networks for big data analytics},
  author = {Wang, Yu and Li, Boxun and Luo, Rong and Chen, Yiran and Xu, Ningyi and Yang, Huazhong},
  booktitle = {Design, Automation and Test in Europe Conference and Exhibition (DATE), 2014},
  pages = {1--2},
  year = {2014},
  organization = {IEEE}
}


@article{wang2014improving,
  title = {Improving Content-based and Hybrid Music Recommendation using Deep Learning},
  author = {Wang, Xinxi and Wang, Ye},
  year = {2014}
}


@inproceedings{wang2014scalable,
  title = {A scalable and topology configurable protocol for distributed parameter synchronization},
  author = {Wang, Minjie and Zhou, Hucheng and Guo, Minyi and Zhang, Zheng},
  booktitle = {Proceedings of 5th Asia-Pacific Workshop on Systems},
  pages = {13},
  year = {2014},
  organization = {ACM}
}


@article{wei2014cnn,
  title = {CNN: Single-label to Multi-label},
  author = {Wei, Yunchao and Xia, Wei and Huang, Junshi and Ni, Bingbing and Dong, Jian and Zhao, Yao and Yan, Shuicheng},
  journal = {arXiv preprint arXiv:1406.5726},
  year = {2014}
}


@incollection{westerlund2014generalized,
  title = {A Generalized Scalable Software Architecture for Analyzing Temporally Structured Big Data in the Cloud},
  author = {Westerlund, Magnus and Hedlund, Ulf and Pulkkis, G{\"o}ran and Bj{\"o}rk, Kaj-Mikael},
  booktitle = {New Perspectives in Information Systems and Technologies, Volume 1},
  pages = {559--569},
  year = {2014},
  publisher = {Springer}
}


@inproceedings{wiesler2014mean,
  title = {Mean-normalized stochastic gradient for large-scale deep learning},
  author = {Wiesler, Simon and Richard, Alexander and Schluter, Ralf and Ney, Hermann},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {180--184},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{wiesler2014rasr,
  title = {RASR/NN: The RWTH neural network toolkit for speech recognition},
  author = {Wiesler, Simon and Richard, Alexander and Golik, Pavel and Schluter, Ralf and Ney, Hermann},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {3281--3285},
  year = {2014},
  organization = {IEEE}
}


@article{wu20143d,
  title = {3D ShapeNets for 2.5 D object recognition and Next-Best-View prediction},
  author = {Wu, Zhirong and Song, Shuran and Khosla, Aditya and Tang, Xiaoou and Xiao, Jianxiong},
  journal = {arXiv preprint arXiv:1406.5670},
  year = {2014}
}


@phdthesis{wu2014human,
  title = {Human Action Recognition Using Deep Probabilistic Graphical Models},
  author = {Wu, Di},
  year = {2014},
  school = {University of Sheffield}
}


@article{xielearning,
  title = {Learning Sparse FRAME Models for Natural Image Patterns},
  author = {Xie, Jianwen and Hu, Wenze and Zhu, Song-Chun and Wu, Ying Nian}
}


@inproceedings{xu2014cross,
  title = {Cross-media relevance mining for evaluating text-based image search engine},
  author = {Xu, Zhongwen and Yang, Yi and Kassim, Ashraf and Yan, Shuicheng},
  booktitle = {Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on},
  pages = {1--4},
  year = {2014},
  organization = {IEEE}
}


@inproceedings{xu2014deep,
  title = {Deep learning of feature representation with multiple instance learning for medical image analysis},
  author = {Xu, Yan and Mo, Tao and Feng, Qiwei and Zhong, Peilin and Lai, Maode and Chang, Eric I and others},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {1626--1630},
  year = {2014},
  organization = {IEEE}
}


@article{xue2014speaker,
  title = {Speaker adaptation of deep neural network based on discriminant codes},
  author = {Xue, Shaofei and Abdel-Hamid, Ossama and Jiang, Hui and Dai, Lirong and Liu, Qingfeng},
  year = {2014},
  publisher = {IEEE}
}


@incollection{yan2014modeling,
  title = {Modeling Video Dynamics with Deep Dynencoder},
  author = {Yan, Xing and Chang, Hong and Shan, Shiguang and Chen, Xilin},
  booktitle = {Computer Vision--ECCV 2014},
  pages = {215--230},
  year = {2014},
  publisher = {Springer}
}


@incollection{yang2014object,
  title = {Object Detection and Viewpoint Estimation with Auto-masking Neural Network},
  author = {Yang, Linjie and Liu, Jianzhuang and Tang, Xiaoou},
  booktitle = {Computer Vision--ECCV 2014},
  pages = {441--455},
  year = {2014}
}


@incollection{yao2014equivalence,
  title = {On the Equivalence Between Deep NADE and Generative Stochastic Networks},
  author = {Yao, Li and Ozair, Sherjil and Cho, Kyunghyun and Bengio, Yoshua},
  booktitle = {Machine Learning and Knowledge Discovery in Databases},
  pages = {322--336},
  year = {2014},
  publisher = {Springer}
}


@article{yi2014shared,
  title = {Shared Representation Learning for Heterogeneous Face Recognition},
  author = {Yi, Dong and Lei, Zhen and Liao, Shengcai and Li, Stan Z},
  journal = {arXiv preprint arXiv:1406.1247},
  year = {2014}
}


@inproceedings{you2014exploring,
  title = {Exploring one pass learning for deep neural network training with averaged stochastic gradient descent},
  author = {You, Zhao and Wang, Xiaorui and Xu, Bo},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {6854--6858},
  year = {2014},
  organization = {IEEE}
}


@article{young2014hierarchical,
  title = {Hierarchical spatiotemporal feature extraction using recurrent online clustering},
  author = {Young, SR and Davis, A and Mishtal, Aaron and Arel, Itamar},
  journal = {Pattern Recognition Letters},
  volume = {37},
  pages = {115--123},
  year = {2014},
  publisher = {Elsevier}
}


@article{young2014impact,
  title = {On the Impact of Approximate Computation in an Analog DeSTIN Architecture},
  author = {Young, Steven and Lu, Junjie and Holleman, Jeremy and Arel, Itamar},
  year = {2014},
  publisher = {IEEE}
}


@misc{yu2014exploiting,
  title = {Exploiting sparseness in training deep neural networks},
  author = {Yu, Dong and Deng, Li and Seide, Frank Torsten Bernd and Li, Gang},
  month = {apr~15},
  year = {2014},
  publisher = {Google Patents}
}


@incollection{zhang2014facial,
  title = {Facial Landmark Detection by Deep Multi-task Learning},
  author = {Zhang, Zhanpeng and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
  booktitle = {Computer Vision--ECCV 2014},
  pages = {94--108},
  year = {2014},
  publisher = {Springer}
}


@inproceedings{zhang2014improving,
  title = {Improving deep neural networks for LVCSR using dropout and shrinking structure},
  author = {Zhang, Shiliang and Bao, Yebo and Zhou, Pan and Jiang, Hui and Dai, Lirong},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {6849--6853},
  year = {2014},
  organization = {IEEE}
}


@article{zhang2014large,
  title = {Large-scale Deep Belief Nets with MapReduce},
  author = {Zhang, KUNLEI and Chen, Xue-wen},
  year = {2014},
  publisher = {IEEE}
}


@article{zhang2014learning,
  title = {Learning ensemble classifiers via restricted Boltzmann machines},
  author = {Zhang, Chun-Xia and Zhang, Jiang-She and Ji, Nan-Nan and Guo, Gao},
  journal = {Pattern Recognition Letters},
  volume = {36},
  pages = {161--170},
  year = {2014},
  publisher = {Elsevier}
}


@inproceedings{zhang2014supervised,
  title = {Supervised deep learning with auxiliary networks},
  author = {Zhang, Junbo and Tian, Guangjian and Mu, Yadong and Fan, Wei},
  booktitle = {Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining},
  pages = {353--361},
  year = {2014},
  organization = {ACM}
}


@article{zhao2014gpu,
  title = {GPU Accelerated Computation and Real-time Rendering of Cellular Automata Model for Spatial Simulation},
  author = {Zhao, Yuan and Zhang, Xinchang and Zhang, Zhen and Wang, Lu and Hu, Yueming},
  year = {2014},
  publisher = {hgpu. org}
}


@article{zhaoautoencoder,
  title = {AN AUTOENCODER WITH BILINGUAL SPARSE FEATURES FOR IMPROVED STATISTICAL MACHINE TRANSLATION},
  author = {Zhao, Bing and Tam, Yik-Cheung and Zheng, Jing}
}


@inproceedings{zheng2014contrastive,
  title = {Contrastive auto-encoder for phoneme recognition},
  author = {Zheng, Xin and Wu, Zhiyong and Meng, Helen and Cai, Lianhong},
  booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  pages = {2529--2533},
  year = {2014},
  organization = {IEEE}
}


@article{zhou2014deep,
  title = {Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction},
  author = {Zhou, Jian and Troyanskaya, Olga G},
  journal = {arXiv preprint arXiv:1403.1347},
  year = {2014}
}


@article{zhu2014deep,
  title = {Deep learning multi-view representation for face recognition},
  author = {Zhu, Zhenyao and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
  journal = {arXiv preprint arXiv:1406.6947},
  year = {2014}
}


@article{zohrer2014single,
  title = {Single Channel Source Separation with General Stochastic Networks},
  author = {Z{\"o}hrer, Matthias and Pernkopf, Franz},
  year = {2014}
}


@article{zou2014generic,
  title = {Generic Object Detection With Dense Neural Patterns and Regionlets},
  author = {Zou, Will Y and Wang, Xiaoyu and Sun, Miao and Lin, Yuanqing},
  journal = {arXiv preprint arXiv:1404.4316},
  year = {2014}
}


@article{zou2014mariana,
  title = {Mariana: Tencent Deep Learning Platform and its Applications},
  author = {Zou, Yongqiang and Jin, Xing and Li, Yi and Guo, Zhimao and Wang, Eryu and Xiao, Bin},
  journal = {Proceedings of the VLDB Endowment},
  volume = {7},
  number = {13},
  year = {2014}
}

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