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Update with 408 recent papers to Deeplearning.University

It has been a while (November 2014) since our last update to the deeplearning bibliography at http://deeplearning.university – but underneath is an update with 408 recent papers (late 2014/early 2015). (This update combined with existing papers will be published to deeplearning.university shortly)

Best regards,
Amund Tveit
(twitter.com/atveit – amund@memkite.com)

Links to Deep Learning Subtopics

[3d] [action recognition] [action recognitionx] [activation functions] [adversarial networks] [age estimation] [algorithm] [animal identification] [applications] [architecture][auto-encoder] [autoencoder] [back propagation] [barcode detection] [bayesian] [bengio] [bifurcated deep network] [big data] [bioinformatics] [biology] [boosting] [bootstrapping] [brain] [caffe] [cancer] [car detection] [cartography] [challenges] [character recognition] [chinese] [clustering] [cognition] [cognitive] [combinatorical optimization] [compression] [consistency] [constructive neural networks] [contour detection] [convex] [convexity] [convoluational neural network] [convolutional network] [convolutional networks] [convolutional neural network] [convolutional neural networks] [cortical processing] [data center] [decision tree] [deep belief network] [deep boltzmann machines] [deep neural network] [deformation] [deformations] [depth estimation] [dermatology] [devops] [diabetic] [dictionary] [digit classification] [disambiguation] [discriminative learning] [disjunctive] [distance functions] [distributed system] [domain invariance] [domain-adversarial] [drone] [dropout] [drug target detection] [economy] [edge detection] [education] [eeg] [electricity] [emotion] [encoding] [encryption] [energy efficient] [evaluation] [event detection] [examination] [extreme learning] [eye tracking] [face recognition] [factorization] [fault diagnosis] [feature extraction] [feature recognition] [feature representation] [feature tuning] [filtering] [fingerprint detection] [fisher vectors] [framework] [frequency domain] [games] [gaussian] [generative deep learning] [gesture recognition] [go] [googlenet] [gpu] [graph] [graphs] [grasping system] [handwriting recognition] [handwritten recognition] [hardware] [helicopter] [high-dimensional data] [hmm] [image classification] [image parsing] [image quality] [image recognition] [image representation] [image segmentation] [improvisation] [induction] [inductive bias] [information theory] [interpolation] [javascript] [kernel] [kernel methods] [kernels] [kickback] [labeling] [lattice] [lecun] [log-likelihood] [low resolution] [matrix] [max pooling] [medical records] [medicine] [memory] [metric] [metric learning] [microblog] [mobile] [mri] [multimedia] [multimodal] [music] [natural language processing] [networking] [neuromorphic] [neuron] [newton] [noise] [non-convex] [numerics] [object classification] [object detection] [object localization] [object recognition] [object reconstruction] [optimization] [orientation estimation] [overview] [parallel] [parameter tuning] [pca] [pedestrian detection] [perception] [photo adjustment] [physics] [platform] [pooling] [posture recognition] [predictive modelling] [prosthetics] [proteinomics] [python] [quality] [quantum computing] [quantum deep learning] [random forests] [ranking] [recommender systems] [recurrant neural networks] [recurrent networks] [regression] [regularization] [reinforcement learning] [reliability] [representation] [representation learning] [restricted boltzmann machine] [restricted boltzmann machines] [retinal images] [reverse annealing] [risk minimization] [robot] [robotics] [salient] [sampling] [scalability] [scene classification] [scene recognition] [score function] [search] [segmentation] [self-informed] [semantic] [semantics] [sentiment analysis] [sequence modelling] [shearlet transform] [signal processing] [similarity learning] [simplicity] [singular value decomposition] [smoothing] [softmax] [software] [sound] [sparseness] [spatial] [spatial planning] [spatio-temporal] [spectral classification] [speech recognition] [speech synthesis] [stability] [statistical inference] [stochastic gradient] [strategiesx] [supervised learning] [surrogates] [survey] [svm] [swarm optimization] [synonym extraction] [target coding] [target detection] [temporal dependencies] [tensor] [text classification] [text recognition] [texture recognition] [theano] [theory] [thin deep networks] [time series] [tools] [topic modelling] [transfer learning] [trends] [ultrasound] [unsupervised learning] [vehicle recognition][weed classification] [wind power] [word segmentation]

3D

  1. Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images
  2. A comparison of 3d shape retrieval methods based on a large-scale benchmark supporting multimodal queries
  3. Deep Learning For Objective Quality Assessment Of 3d Images
  4. Designing Deep Networks for Surface Normal Estimation
  5. TriViews: A general framework to use 3d depth data effectively for action recognition
  6. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners
  7. C3d: Generic Features for Video Analysis
  8. Semantic Volume Segmentation with Iterative Context Integration

 

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

 

Activation Functions

  1. Learning Activation Functions to Improve Deep Neural Networks

 

Adversarial Networks

  1. Conditional Generative Adversarial Nets

 

Age Estimation

  1. Age Estimation by Multi-scale Convolutional Network

 

Algorithm

  1. Bimmer: a novel algorithm for detecting differential Dna methylation regions from MBDCap-seq data
  2. Set-label modeling and deep metric learning on person re-identification
  3. Stacked Quantizers for Compositional Vector Compression
  4. SelfieBoost: A Boosting Algorithm for Deep Learning
  5. Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
  6. Supervised non-negative matrix factorization for audio source separation
  7. Multiscale Centerline Detection
  8. A Convex Formulation for Spectral Shrunk Clustering
  9. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates
  10. The Loss Surface of Multilayer Networks
  11. Cross-Modal Learning via Pairwise Constraints
  12. An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
  13. Support Vector-Based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification
  14. Online Bandit Learning for a Special Class of Non-convex Losses
  15. A twice face recognition algorithm
  16. Implementation of Evolutionary Algorithms for Deep Architectures
  17. Stochastic Descent Analysis of Representation Learning Algorithms
  18. Preliminary evaluation of hyperopt algorithms on HPOLib
  19. Class Margins: Learning to (Un) Learn

 

Animal Identification

  1. Automatic Animal Species Identification Based on Camera Trapping Data

 

Applications

  1. Machine Learning for Medical Applications
  2. Extreme learning machines: new trends and applications

 

Architecture

  1. Unisense: A Unified and Sustainable Sensing and Transport Architecture for Large Scale and Heterogeneous Sensor Networks
  2. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
  3. Da-ccd: A novel action representation by deep architecture of local depth feature
  4. Review of Advances in Neural Networks: Neural Design Technology Stack
  5. An Adaptive Stacked Denoising Auto-Encoder Architecture for Human Action Recognition
  6. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  7. Towards Deep Neural Network Architectures Robust to Adversarial Examples
  8. Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology
  9. Implementation of Evolutionary Algorithms for Deep Architectures
  10. Visual Scene Representations: Scaling and Occlusion in Convolutional Architectures
  11. Obtaining Cross-modal Similarity Metric with Deep Neural Architecture
  12. Hierarchical reinforcement learning in a biologically plausible neural architecture

 

Audio

  1. Supervised non-negative matrix factorization for audio source separation
  2. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition
  3. Convolutional Data: Towards Deep Audio Learning from Big Data
  4. Physiologic Audio Fingerprinting

 

Auto-Encoder

  1. Topic-aware Deep Auto-encoders (tda) for Face Alignment
  2. An Adaptive Stacked Denoising Auto-Encoder Architecture for Human Action Recognition

 

Autoencoder

  1. Relational Stacked Denoising Autoencoder for Tag Recommendation
  2. Learning Feature Representations with a Cost-Relevant Sparse Autoencoder
  3. Introduction to Autoencoders
  4. Multimodal Video Classification with Stacked Contractive Autoencoders

 

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

 

Barcode Detection

  1. Real-time Barcode Detection in the Wild

 

Bayesian

  1. A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis
  2. Bayesian Deep Deconvolutional Learning

 

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 Data

  1. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  2. Practice in Synonym Extraction at Large Scale
  3. Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology
  4. Convolutional Data: Towards Deep Audio Learning from Big Data

 

Bioinformatics

  1. Automated computation of arbor densities: a step toward identifying neuronal cell types
  2. Improved contact predictions using the recognition of protein like contact patterns.
  3. Automated Gene Expression Pattern Annotation In The Mouse Brain
  4. Bimmer: a novel algorithm for detecting differential Dna methylation regions from MBDCap-seq data
  5. Possible computational filter to detect proteins associated to influenza A subtype H1n1.
  6. Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data
  7. Deep Belief Networks and Biomedical Text Categorisation
  8. lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning
  9. Comparative Study Of Machine Learning Techniques For Supervised Classification Of Biomedical Data
  10. An Innovative Svm for Wheat Seed Quality Estimation⋆

 

Biology

  1. What We Can Learn From the Primate’s Visual System

 

Boosting

  1. SelfieBoost: A Boosting Algorithm for Deep Learning

 

Bootstrapping

  1. Training Deep Neural Networks on Noisy Labels with Bootstrapping

 

Brain

  1. Automated Gene Expression Pattern Annotation In The Mouse Brain
  2. Deep Extreme Learning Machine and Its Application in Eeg Classification
  3. Brain Ct Image Classification with Deep Neural Networks
  4. Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function
  5. Hardware-Amenable Structural Learning for Spike-based Pattern Classification using a Simple Model of Active Dendrites
  6. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  7. Learning Deep Temporal Representations for Brain Decoding
  8. Brain Edge Detection
  9. Methodology and Techniques for Building Modular Brain-Computer Interfaces
  10. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation
  11. Pain: a distributed brain information network?

 

Caffe

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

 

Cancer

  1. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach
  2. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  3. Cancerous Cell Detection Using Histopathological Image Analysis
  4. Color Correction Arrangements For Dermoscopy
  5. Methods And Arrangements For Identifying Dermatological Diagnoses With Clinically Negligible Probabilties

 

Car Detection

  1. Joint Deep Learning for Car Detection

 

Cartography

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

 

Challenges

  1. Neural-Symbolic Learning and Reasoning: Contributions and Challenges
  2. The quality and reputation of open, distance and e-learning: what are the challenges?

 

Character Recognition

  1. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  2. Robust Multi-Layer Hierarchical Model for Digit Character Recognition

 

Chinese

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

 

Clustering

  1. A Convex Formulation for Spectral Shrunk Clustering
  2. Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering
  3. Improving relation descriptor extraction with word embeddings and cluster features
  4. SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering
  5. Soft context clustering for F0 modeling in HMM-based speech synthesis
  6. Deep Learning with Nonparametric Clustering

 

Cognition

  1. Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment

 

Cognitive

  1. Potential of Cognitive Computing and Cognitive Systems

 

Combinatorical Optimization

  1. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization

 

Compression

  1. Stacked Quantizers for Compositional Vector Compression

 

Consistency

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

 

Constructive Neural Networks

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

 

Contour Detection

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

 

Convex

  1. A Convex Formulation for Spectral Shrunk Clustering

 

Convexity

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

 

Convoluational Neural Network

  1. Permutohedral Lattice CNNs

 

Convolutional Network

  1. A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks
  2. Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns
  3. Efficient Object Localization Using Convolutional Networks
  4. Long-term Recurrent Convolutional Networks for Visual Recognition and Description
  5. Fully Convolutional Networks for Semantic Segmentation
  6. Deep Deconvolutional Networks for Scene Parsing
  7. Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection
  8. Age Estimation by Multi-scale Convolutional Network
  9. Memory Bounded Deep Convolutional Networks
  10. Real-time object recognition and orientation estimation using an event-based camera and Cnn
  11. Occlusion Edge Detection in Rgb-d Frames using Deep Convolutional Networks
  12. Image Super-Resolution Using Deep Convolutional Networks

 

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. Fully Convolutional Neural Networks for Crowd Segmentation
  2. Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition
  3. Visual Sentiment Prediction with Deep Convolutional Neural Networks
  4. Learning to Generate Chairs with Convolutional Neural Networks
  5. The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
  6. Scene Recognition Using Mid-level features from Cnn
  7. Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
  8. Convolutional Neural Networks at Constrained Time Cost
  9. Image Recognition Using Convolutional Neural Networks
  10. Reading Text in the Wild with Convolutional Neural Networks
  11. Real-Time Grasp Detection Using Convolutional Neural Networks
  12. Teaching Deep Convolutional Neural Networks to Play Go
  13. Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification
  14. DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection
  15. Learning Block Group Sparse Representation Combined with Convolutional Neural Networks for Rgb-d Object Recognition
  16. Bayesian Deep Deconvolutional Learning
  17. Flattened Convolutional Neural Networks for Feedforward Acceleration
  18. Move Evaluation In Go Using Deep Convolutional Neural Networks
  19. Robotic Grasping System Using Convolutional Neural Networks
  20. Fully Convolutional Multi-Class Multiple Instance Learning
  21. Striving for Simplicity: The All Convolutional Net
  22. Learning Compact Convolutional Neural Networks with Nested Dropout
  23. Visual Scene Representations: Scaling and Occlusion in Convolutional Architectures
  24. Learning linearly separable features for speech recognition using convolutional neural networks
  25. Generative Modeling of Convolutional Neural Networks
  26. Spectral classification using convolutional neural networks
  27. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

 

Convolutional Neural Networks

  1. Combining the Best of Graphical Models and ConvNets for Semantic Segmentation
  2. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

 

Cortical Processing

  1. Correlated activity supports efficient cortical processing

 

Data Center

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

 

Decision Tree

  1. Clinical Decision Analysis using Decision Tree

 

Deep Belief Network

  1. A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks
  2. Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images
  3. Deep Belief Network Training Improvement Using Elite Samples Minimizing Free Energy
  4. Systems and methods for analyzing data using deep belief networks (dbn) and identifying a pattern in a graph
  5. Deep Belief Networks and Biomedical Text Categorisation
  6. Unsupervised feature learning on monaural Doa estimation using convolutional deep belief networks
  7. A Study of Deep Belief Network Based Chinese Speech Emotion Recognition
  8. Auditory Scene Classification with Deep Belief Network

 

Deep Boltzmann Machines

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

 

Deep Neural Network

  1. How transferable are features in deep neural networks?
  2. Deep Neural Network Based Speech Separation for Robust Speech Recognition
  3. An Optimization of Deep Neural Networks in Asr using Singular Value Decomposition
  4. Speech Separation of A Target Speaker Based on Deep Neural Networks
  5. Real-time Head Orientation from a Monocular Camera using Deep Neural Network
  6. Deep Neural Networks
  7. Brain Ct Image Classification with Deep Neural Networks
  8. Feature Representation Learning in Deep Neural Networks
  9. Representation Sharing and Transfer in Deep Neural Networks
  10. Deep Neural Network-Hidden Markov Model Hybrid Systems
  11. Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features
  12. A Survey of Regularization Methods for Deep Neural Network
  13. Environmentally robust Asr front-end for deep neural network acoustic models
  14. Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
  15. Object Recognition Using Deep Neural Networks: A Survey
  16. Supplementary Material: On the Number of Linear Regions of Deep Neural Networks
  17. No-reference image quality assessment with shearlet transform and deep neural Networks
  18. Deep neural network adaptation for children’s and adults’ speech recognition
  19. Towards Deep Neural Network Architectures Robust to Adversarial Examples
  20. Fixed-point feedforward deep neural network design using weights+ 1, 0, and− 1
  21. Learning Activation Functions to Improve Deep Neural Networks
  22. Training Deep Neural Networks on Noisy Labels with Bootstrapping
  23. Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks
  24. An analysis of deep neural networks for texture classification
  25. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers
  26. Fast adaptation of deep neural network based on discriminant codes for speech recognition

 

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

 

Depth Estimation

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

 

Dermatology

  1. Gesture-based Dermatologic Data Collection And Presentation

 

Devops

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

 

Diabetic

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

 

Dictionary

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

 

Digit Classification

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

 

Disambiguation

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

 

Discriminative Learning

  1. Matrix and Tensor Features for Discriminative Learning

 

Disjunctive

  1. Disjunctive Normal Networks

 

Distance Functions

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

 

Distributed System

  1. Distributed Training of Neural Network Language Models

 

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. On the Inductive Bias of Dropout
  2. Learning Compact Convolutional Neural Networks with Nested Dropout

 

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. Predicting Academic Achievement of High-School Students Using Machine Learning

 

Eeg

  1. Deep Extreme Learning Machine and Its Application in Eeg Classification
  2. Learning Deep Temporal Representations for Brain Decoding
  3. Methodology and Techniques for Building Modular Brain-Computer Interfaces

 

Electricity

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

 

Emotion

  1. Emotion Modeling and Machine Learning in Affective Computing
  2. Emotion Recognition in the Wild with Feature Fusion and Multiple Kernel Learning
  3. A Study of Deep Belief Network Based Chinese Speech Emotion Recognition

 

Encoding

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

 

Encryption

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

 

Energy Efficient

  1. Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition
  2. Stt-snn: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks

 

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 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

 

Extreme Learning

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

 

Eye Tracking

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

 

Face Recognition

  1. Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations
  2. Set-label modeling and deep metric learning on person re-identification
  3. Automatic face annotation in Tv series by video/script alignment
  4. Real-time Head Orientation from a Monocular Camera using Deep Neural Network
  5. Topic-aware Deep Auto-encoders (tda) for Face Alignment
  6. Deep Learning Face Attributes in the Wild
  7. Effective Face Frontalization in Unconstrained Images
  8. Learning Face Representation from Scratch
  9. Deeply learned face representations are sparse, selective, and robust
  10. Shared features for multiple face-based biometrics
  11. A twice face recognition algorithm
  12. Feature Selection And Extraction For Babyface Recognition
  13. Personalized Face Image Retrieval Based On Gmkl
  14. Software Quality Evaluation of Face Recognition APIs & Libraries
  15. Online Smart Face Morphing Engine with Prior Constraints and Local Geometry Preservation
  16. A Learning Framework for Age Rank Estimation based on Face Images with Scattering Transform
  17. Privileged Information-based Conditional Structured Output Regression Forest for Facial Point Detection

 

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 Extraction

  1. Pre-release sales forecasting: A model-driven context feature extraction approach
  2. Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection
  3. Da-ccd: A novel action representation by deep architecture of local depth feature
  4. Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering
  5. Wind Power Prediction and Pattern Feature Based on Deep Learning Method
  6. Geodesic Invariant Feature (gif): A Local Descriptor in Depth
  7. Prototype-Based Discriminative Feature Learning for Kinship Verification
  8. Visual Causal Feature Learning
  9. Matrix and Tensor Features for Discriminative Learning
  10. Integrating Stroke-distribution Information Into Spatial Feature Extraction For Automatic Handwriting Recognition
  11. Feature Weight Tuning for Recursive Neural Networks
  12. Score Function Features for Discriminative Learning: Matrix and Tensor Framework
  13. Sparse, guided feature connections in an Abstract Deep Network
  14. Exploiting high level feature for dynamic textures recognition
  15. Learning Feature Representations with a Cost-Relevant Sparse Autoencoder
  16. Feature Selection And Extraction For Babyface Recognition
  17. Learning linearly separable features for speech recognition using convolutional neural networks
  18. C-SVDDNet: An Effective Single-Layer Network for Unsupervised Feature Learning
  19. View-independent object detection using shared local features
  20. lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning
  21. Unsupervised Feature Learning for Dense Correspondences across Scenes
  22. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression

 

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 Tuning

  1. Feature Weight Tuning for Recursive Neural Networks

 

Filtering

  1. Depth of field rendering via adaptive recursive filtering

 

Fingerprint Detection

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

 

Fisher Vectors

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

 

Font Recognition

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

 

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

 

Frequency Domain

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

 

Games

  1. Learning with serious games: is fun playing the game a predictor of learning success?
  2. Teaching Deep Convolutional Neural Networks to Play Go
  3. Move Evaluation In Go Using Deep Convolutional Neural Networks

 

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

 

Generative Deep Learning

  1. Implementation of discriminative and generative deep learning

 

Gesture Recognition

  1. A hierarchical structure for gesture recognition using Rgb-d sensor
  2. 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 GPGPU-Based Acceleration of Fault-Tolerant Mlp Learnings
  2. Theano-based Large-Scale Visual Recognition with Multiple GPUs
  3. A Gpu Implementation of GoogLeNet

 

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

 

Graphs

  1. Learning Word Representations from Relational Graphs

 

Grasping System

  1. Advanced Robotic Grasping System Using Deep Learning

 

Handwriting Recognition

  1. Managing Real-time Handwriting Recognition
  2. Real-time Stroke-order And Stroke-direction Independent Handwriting Recognition
  3. Multi-script Handwriting Recognition Using A Universal Recognizer

 

Handwritten Recognition

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

 

Hardware

  1. Back-Propagation Operation for Analog Neural Network Hardware with Synapse Components Having Hysteresis Characteristics
  2. Hardware-Amenable Structural Learning for Spike-based Pattern Classification using a Simple Model of Active Dendrites
  3. A Biological-Realtime Neuromorphic System in 28 nm Cmos using Low-Leakage Switched Capacitor Circuits

 

Helicopter

  1. Machine Learning for Helicopter Dynamics Models

 

High-Dimensional Data

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

 

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

 

Image Classification

  1. Combining Newton interpolation and deep learning for image classification

 

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. Handwritten Digits Classification
  2. MatchBox: Indoor Image Matching via Box-like Scene Estimation
  3. Understanding image representations by measuring their equivariance and equivalence
  4. Hypercolumns for Object Segmentation and Fine-grained Localization
  5. The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
  6. A deep Hmm model for multiple keywords spotting in handwritten documents
  7. Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation
  8. Visual Scene Representations: Sufficiency, Minimality, Invariance and Approximations
  9. Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a Uav
  10. Image Recognition Using Convolutional Neural Networks
  11. Image Super-Resolution Using Deep Convolutional Networks
  12. Bikers are like tobacco shops, formal dressers are like suits: Recognizing Urban Tribes with Caffe

 

Image Representation

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

 

Image Segmentation

  1. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
  2. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

 

Improvisation

  1. Machine Learning Applied to Musical Improvisation

 

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 Theory

  1. An Information Theoretic Approach to Quantifying Text Interestingness

 

Interpolation

  1. Combining Newton interpolation and deep learning for image classification

 

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

 

Kernel Methods

  1. 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

 

Kickback

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

 

Labeling

  1. Sequential Labeling with online Deep Learning

 

Lattice

  1. Permutohedral Lattice CNNs

 

Lecun

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

 

Log-Likelihood

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

 

Low Resolution

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

 

Matrix

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

 

Max Pooling

  1. Fractional Max-Pooling

 

Medical Records

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

 

Medicine

  1. Clinical Decision Analysis using Decision Tree
  2. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners
  3. Signal Processing in Next-Generation Prosthetics [Special Reports]
  4. Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach
  5. Machine Learning for Medical Applications
  6. Adapting Linguistic Tools for the Analysis of Italian Medical Records
  7. Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
  8. Learning Deep Temporal Representations for Brain Decoding
  9. Cancerous Cell Detection Using Histopathological Image Analysis
  10. Dermoscopic Data Acquisition Employing Display Illumination
  11. Gesture-based Dermatologic Data Collection And Presentation
  12. Color Correction Arrangements For Dermoscopy
  13. Methods And Arrangements For Identifying Dermatological Diagnoses With Clinically Negligible Probabilties

 

Memory

  1. Memory Bounded Deep Convolutional Networks

 

Metric

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

 

Metric Learning

  1. Deep metric learning using Triplet network

 

Microblog

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

 

Mobile

  1. Travel Behavior Characterization Using Raw Accelerometer Data Collected from Smartphones
  2. Stt-snn: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks
  3. Can Deep Learning Revolutionize Mobile Sensing?

 

Mri

  1. Brain Edge Detection

 

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. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition
  2. Machine Learning Applied to Musical Improvisation

 

Natural Language Processing

  1. Deep Recursive Neural Networks for Compositionality in Language
  2. Text Mining with the Stanford CoreNLP
  3. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
  4. From Captions to Visual Concepts and Back
  5. Show and Tell: A Neural Image Caption Generator
  6. Deep Belief Networks and Biomedical Text Categorisation
  7. Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
  8. Deep Learning for Answer Sentence Selection
  9. Improving relation descriptor extraction with word embeddings and cluster features
  10. Practice in Synonym Extraction at Large Scale
  11. Reading Text in the Wild with Convolutional Neural Networks
  12. Learning Word Representations from Relational Graphs
  13. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning
  14. An Information Theoretic Approach to Quantifying Text Interestingness
  15. Adapting Linguistic Tools for the Analysis of Italian Medical Records
  16. Translating Videos to Natural Language Using Deep Recurrent Neural Networks
  17. Data collection and language understanding of food descriptions
  18. Cnu System in Ntcir-11 IMine Task
  19. Tuta1 at the Ntcir-11 IMine Task

 

Networking

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

 

Neuromorphic

  1. A neuromorphic categorization system with Online Sequential Extreme Learning
  2. 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

 

Newton

  1. Combining Newton interpolation and deep learning for image classification

 

Noise

  1. Training Deep Neural Networks on Noisy Labels with Bootstrapping

 

Non-Convex

  1. Online Bandit Learning for a Special Class of Non-convex Losses

 

Numerics

  1. 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. Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection
  2. Analysis of Multilayer Neural Networks for Object Recognition
  3. Real-time object recognition and orientation estimation using an event-based camera and Cnn

 

Object Reconstruction

  1. Virtual View Networks for Object Reconstruction

 

Optimization

  1. The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks
  2. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates
  3. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
  4. Convolutional Neural Networks at Constrained Time Cost
  5. Memory Bounded Deep Convolutional Networks
  6. Sparse Representations, Numerical Linear Algebra, and Optimization

 

Orientation Estimation

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

 

Overview

  1. Deep Learning
  2. An Anarchy of Methods: Current Trends in How Intelligence Is Abstracted in Ai
  3. An Overview of Deep Generative Models

 

Parallel

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

 

Parameter Tuning

  1. Predicting parameters in deep learning

 

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

 

Perception

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

 

Photo Adjustment

  1. Automatic Photo Adjustment Using Deep Learning

 

Physics

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

 

Platform

  1. 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

 

Posture Recognition

  1. A Biologically Inspired Human Posture Recognition System

 

Predictive Modelling

  1. Hybrid Predictive Model For Enhancing Prosodic Expressiveness

 

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 Computing

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

 

Quantum Deep Learning

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

 

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

 

Recommender Systems

  1. Cars2: Learning Context-aware Representations for Context-aware Recommendations
  2. Deep Exponential Families

 

Recurrant Neural Networks

  1. Translating Videos to Natural Language Using Deep Recurrent Neural Networks

 

Recurrent Networks

  1. Recurrent Neural Networks and Related Models

 

Regression

  1. A Deep and Stable Extreme Learning Approach for Classification and Regression
  2. Transparent-supported radiance regression function

 

Regularization

  1. A Survey of Regularization Methods for Deep Neural Network
  2. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
  3. Neural Network Regularization via Robust Weight Factorization

 

Reinforcement Learning

  1. Hierarchical reinforcement learning in a biologically plausible neural architecture

 

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

 

Restricted Boltzmann Machine

  1. Deep Correspondence Restricted Boltzmann Machine for Cross-modal Retrieval
  2. A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling

 

Restricted Boltzmann Machines

  1. Scalable Learning for Restricted Boltzmann Machines
  2. Atomic Energy Models For Machine Learning: Atomic Restricted Boltzmann Machines
  3. A Distributed Implementation of Training the Restricted Boltzmann Machine
  4. Energy Based Models and Boltzmann Machines (Cont.)
  5. Deep Narrow Boltzmann Machines are Universal Approximators
  6. Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
  7. An automatic setting for training restricted boltzmann machine
  8. An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
  9. Restricted Boltzmann Machines with Svm for Object Recognition⋆
  10. Voice Conversion Using Rnn Pre-Trained by Recurrent Temporal Restricted Boltzmann Machines
  11. Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning
  12. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines

 

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

 

Risk Minimization

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

 

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

 

Robotics

  1. Control In A Safe Set: Addressing Safety In Human-robot Interactions

 

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?

 

Scalability

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

 

Scene Classification

  1. Scene Classification Based on Single-layer Sae and Svm

 

Scene Recognition

  1. Deep Deconvolutional Networks for Scene Parsing
  2. Scene Recognition Using Mid-level features from Cnn
  3. Scene Recognition

 

Score Function

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

 

Search

  1. Beginning at the End: The outcome spaces framework to guide purposive transdisciplinary research
  2. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
  3. The Research of Event Detection and Characterization Technology of Ticket Gate in the Urban Rapid Rail Transit

 

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

 

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

 

Semantics

  1. Learning Multi-Relational Semantics Using Neural-Embedding Models

 

Sentiment Analysis

  1. Visual Sentiment Prediction with Deep Convolutional Neural Networks

 

Sequence Modelling

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

 

Shearlet Transform

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

 

Singular Value Decomposition

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

 

Smoothing

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

 

Softmax

  1. Quaternion softmax classifier

 

Software

  1. Software Quality Evaluation of Face Recognition APIs & Libraries

 

Sound

  1. Estimating Tract Variables from Acoustics via Neural Networks
  2. Supervised non-negative matrix factorization for audio source separation
  3. Multilabel Sound Event Classification with Neural Networks
  4. Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition

 

Sparseness

  1. Sparse Representations, Numerical Linear Algebra, and Optimization
  2. Provable Methods for Training Neural Networks with Sparse Connectivity
  3. Sparse Deep Stacking Network for Image Classification

 

Spatial

  1. The Spatial Complexity of Inhomogeneous Multi-layer Neural Networks

 

Spatial Planning

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

 

Spatio-Temporal

  1. Learning spatio-temporal features for action recognition from the side of the video
  2. Spatio-Temporal Moving Object Proposals

 

Spectral Classification

  1. Spectral classification using convolutional neural networks

 

Speech Recognition

  1. Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding
  2. Supervised Speech Separation And Processing
  3. Deep Neural Network Based Speech Separation for Robust Speech Recognition
  4. Speech Separation of A Target Speaker Based on Deep Neural Networks
  5. Extracting Deep Bottleneck Features For Visual Speech Recognition
  6. A critical examination of deep learning approaches to automated speech recognition
  7. End-to-end Continuous Speech Recognition using Attention-based Recurrent Nn: First Results
  8. Automatic Speech Recognition: A Deep Learning Approach
  9. Deep neural network adaptation for children’s and adults’ speech recognition
  10. Vocal Tract Length Normalisation Approaches To Dnn-based Children’s And Adults’speech Recognition
  11. Audio-visual speech recognition using deep learning
  12. DeepSpeech: Scaling up end-to-end speech recognition
  13. Learning linearly separable features for speech recognition using convolutional neural networks
  14. Speech Enhancement Based on Analysis–Synthesis Framework With Improved Pitch Estimation and Spectral Envelope Enhancement
  15. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers
  16. Soft context clustering for F0 modeling in HMM-based speech synthesis
  17. Fast adaptation of deep neural network based on discriminant codes for speech recognition

 

Speech Synthesis

  1. Parametric Speech Synthesis Using Local and Global Sparse Gaussian

 

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 Gradient

  1. Stochastic Descent Analysis of Representation Learning Algorithms
  2. Deep learning with Elastic Averaging Sgd
  3. Adasecant: Robust Adaptive Secant Method for Stochastic Gradient
  4. Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods

 

Strategiesx

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

 

Supervised Learning

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

 

Surrogates

  1. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates

 

Survey

  1. A Survey of Regularization Methods for Deep Neural Network
  2. An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey
  3. Object Recognition Using Deep Neural Networks: A Survey
  4. Survey of Local Descriptor of Object Recognition System based on Rgb-d Images
  5. Non-Distortion-Specific no-reference image quality assessment: A survey
  6. Comparative Study Of Machine Learning Techniques For Supervised Classification Of Biomedical Data

 

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⋆

 

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 Dependencies

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

 

Tensor

  1. Matrix and Tensor Features for Discriminative Learning

 

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. Supplementary Material: On the Number of Linear Regions of Deep Neural Networks
  2. Why does Deep Learning work?-A perspective from Group Theory

 

Thin Deep Networks

  1. FitNets: Hints for Thin Deep Nets

 

Time Series

  1. Dual-domain Hierarchical Classification of Phonetic Time Series
  2. Support Vector-Based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification
  3. Error Modeling Approach to Improve Time Series Forecasters

 

Tools

  1. R for Cloud Computing

 

Topic Modelling

  1. A Novel Neural Topic Model and Its Supervised Extension

 

Transfer Learning

  1. Deep Multi-Instance Transfer Learning
  2. Representation Sharing and Transfer in Deep Neural Networks
  3. Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers

 

Trends

  1. Foundations and Trends® in Computer Graphics and Vision

 

Ultrasound

  1. High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners

 

Unsupervised Learning

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

 

Vehicle Recognition

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

 

Video

  1. Automatic face annotation in Tv series by video/script alignment
  2. Building a Post-Compression Region-of-Interest Encryption Framework for Existing Video Surveillance Systems
  3. Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web
  4. C3d: Generic Features for Video Analysis
  5. Video Event Detection via Multi-modality Deep Learning
  6. Audio-based annnotatoion of video
  7. Translating Videos to Natural Language Using Deep Recurrent Neural Networks

 

Weed Classification

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

 

Wind Power

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

 

Word Segmentation

  1. Learning Character Representations for Chinese Word Segmentation

 

BIBLIOGRAPHY

@misc{2014AAGarcezTRBesoldLdeRaedtPFöldiakPHitzler,
  title = {Neural-Symbolic Learning and Reasoning: Contributions and Challenges},
  author = {AA Garcez, TR Besold, L de Raedt, P Földiak, P Hitzler}
}


@misc{2014AChoromanskaMHenaffMMathieuGBArous,
  title = {The Loss Surface of Multilayer Networks},
  author = {A Choromanska, M Henaff, M Mathieu, GB Arous}
}


@misc{2014ADosovitskiyJTSpringenbergTBrox,
  title = {Learning to Generate Chairs with Convolutional Neural Networks},
  author = {A Dosovitskiy, JT Springenberg, T Brox}
}


@misc{2014ADroniouSIvaldiOSigaud,
  title = {Deep unsupervised network for multimodal perception, representation and classification},
  author = {A Droniou, S Ivaldi, O Sigaud}
}


@misc{2014AGaskellRMills,
  title = {The quality and reputation of open, distance and e-learning: what are the challenges?},
  author = {A Gaskell, R Mills}
}


@misc{2014AHannunCCaseJCasperBCatanzaroGDiamos,
  title = {DeepSpeech: Scaling up end-to-end speech recognition},
  author = {A Hannun, C Case, J Casper, B Catanzaro, G Diamos}
}


@misc{2014AJYepesAMacKinlayJBedoRGarnaviQChen,
  title = {Deep Belief Networks and Biomedical Text Categorisation},
  author = {AJ Yepes, A MacKinlay, J Bedo, R Garnavi, Q Chen}
}


@misc{2014AJainSAteySVinayakVSrivastava,
  title = {Cancerous Cell Detection Using Histopathological Image Analysis},
  author = {A Jain, S Atey, S Vinayak, V Srivastava}
}


@misc{2014AKNoor,
  title = {Potential of Cognitive Computing and Cognitive Systems},
  author = {AK Noor}
}


@misc{2014AKnittelABlair,
  title = {Sparse, guided feature connections in an Abstract Deep Network},
  author = {A Knittel, A Blair}
}


@misc{2014ANguyenJYosinskiJClune,
  title = {Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images},
  author = {A Nguyen, J Yosinski, J Clune}
}


@misc{2014AOhri,
  title = {R for Cloud Computing},
  author = {A Ohri}
}


@misc{2014APaulSVenkatasubramanian,
  title = {Why does Deep Learning work?-A perspective from Group Theory},
  author = {A Paul, S Venkatasubramanian}
}


@misc{2014APunjaniPAbbeel,
  title = {Machine Learning for Helicopter Dynamics Models},
  author = {A Punjani, P Abbeel}
}


@misc{2014ARodríguezSánchezHNeumannJPiater,
  title = {Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects},
  author = {A Rodríguez-Sánchez, H Neumann, J Piater}
}


@misc{2014ARomeroNBallasSEKahouAChassangCGatta,
  title = {FitNets: Hints for Thin Deep Nets},
  author = {A Romero, N Ballas, SE Kahou, A Chassang, C Gatta}
}


@misc{2014ASRazavianHAzizpourAMakiJSullivanCHEk,
  title = {Persistent Evidence of Local Image Properties in Generic ConvNets},
  author = {AS Razavian, H Azizpour, A Maki, J Sullivan, CH Ek}
}


@misc{2014ASinghARajVKGupta,
  title = {Scene Recognition Using Mid-level features from Cnn},
  author = {A Singh, A Raj, VK Gupta}
}


@misc{2014ASinghARajVKGuptaSceneRecognition,
  title = {Scene Recognition},
  author = {A Singh, A Raj, VK Gupta}
}


@misc{2014ASironiETüretkenVLepetitPFua,
  title = {Multiscale Centerline Detection},
  author = {A Sironi, E Türetken, V Lepetit, P Fua}
}


@misc{2014AUnterwegerKVanRyckegemDEngelAUhl,
  title = {Building a Post-Compression Region-of-Interest Encryption Framework for Existing Video Surveillance Systems},
  author = {A Unterweger, K Van Ryckegem, D Engel, A Uhl}
}


@misc{2014BAhnJParkISKweon,
  title = {Real-time Head Orientation from a Monocular Camera using Deep Neural Network},
  author = {B Ahn, J Park, IS Kweon}
}


@misc{2014BCKoJHJungJYNam,
  title = {View-independent object detection using shared local features},
  author = {BC Ko, JH Jung, JY Nam}
}


@misc{2014BChenQYinPGuo,
  title = {A Study of Deep Belief Network Based Chinese Speech Emotion Recognition},
  author = {B Chen, Q Yin, P Guo}
}


@misc{2014BEJuel,
  title = {Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning},
  author = {BE Juel}
}


@misc{2014BElizaldeMRavanelliKNiDBorthGFriedland,
  title = {Audio-Concept Features and Hidden Markov Models for Multimedia Event Detection},
  author = {B Elizalde, M Ravanelli, K Ni, D Borth, G Friedland}
}


@misc{2014BGraham,
  title = {Fractional Max-Pooling},
  author = {B Graham}
}


@misc{2014BHariharanPArbeláezRGirshickJMalik,
  title = {Hypercolumns for Object Segmentation and Fine-grained Localization},
  author = {B Hariharan, P Arbeláez, R Girshick, J Malik}
}


@misc{2014BKleinGLevGSadehLWolf,
  title = {Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation},
  author = {B Klein, G Lev, G Sadeh, L Wolf}
}


@misc{2014BLDavisTFRodriguezAMReedJStachColorCorrectionArrangements,
  title = {Color Correction Arrangements For Dermoscopy},
  author = {BL Davis, TF Rodriguez, AM Reed, J Stach}
}


@misc{2014BLDavisTFRodriguezAMReedJStachGesture-basedDermatologicData,
  title = {Gesture-based Dermatologic Data Collection And Presentation},
  author = {BL Davis, TF Rodriguez, AM Reed, J Stach}
}


@misc{2014BLDavisTFRodriguezAMReedJStachMethodsAndArrangements,
  title = {Methods And Arrangements For Identifying Dermatological Diagnoses With Clinically Negligible Probabilties},
  author = {BL Davis, TF Rodriguez, AM Reed, J Stach}
}


@misc{2014BLDavisTFRodriguezAMReedJStachPhysiologicAudioFingerprinting,
  title = {Physiologic Audio Fingerprinting},
  author = {BL Davis, TF Rodriguez, AM Reed, J Stach}
}


@misc{2014BLiYLuCLiAGodilTSchreckMAono,
  title = {A comparison of 3d shape retrieval methods based on a large-scale benchmark supporting multimodal queries},
  author = {B Li, Y Lu, C Li, A Godil, T Schreck, M Aono}
}


@misc{2014BLiuFMoJTao,
  title = {Speech Enhancement Based on Analysis–Synthesis Framework With Improved Pitch Estimation and Spectral Envelope Enhancement},
  author = {B Liu, F Mo, J Tao}
}


@misc{2014BMettlerZKongBLiJAndersh,
  title = {Systems View on Spatial Planning and Perception Based on Invariants in Agent-Environment Dynamics},
  author = {B Mettler, Z Kong, B Li, J Andersh}
}


@misc{2014BNeyshaburRTomiokaNSrebro,
  title = {In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning},
  author = {B Neyshabur, R Tomioka, N Srebro}
}


@misc{2014BPooleSEDU,
  title = {Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods},
  author = {B Poole, S EDU}
}


@misc{2014BShakibi,
  title = {Predicting parameters in deep learning},
  author = {B Shakibi}
}


@misc{2014BWang,
  title = {Automatic Animal Species Identification Based on Camera Trapping Data},
  author = {B Wang}
}


@misc{2014BYangWYihXHeJGaoLDeng,
  title = {Learning Multi-Relational Semantics Using Neural-Embedding Models},
  author = {B Yang, W Yih, X He, J Gao, L Deng}
}


@misc{2014BÇAydınEKarasakalCİyigün,
  title = {A Probabilistic Multiple Criteria Sorting Approach Based On Distance Functions},
  author = {BÇ Aydın, E Karasakal, C İyigün}
}


@misc{2014CClarkAStorkey,
  title = {Teaching Deep Convolutional Neural Networks to Play Go},
  author = {C Clark, A Storkey}
}


@misc{2014CCreusotAMunawar,
  title = {Real-time Barcode Detection in the Wild},
  author = {C Creusot, A Munawar}
}


@misc{2014CDaHZhangYSang,
  title = {Brain Ct Image Classification with Deep Neural Networks},
  author = {C Da, H Zhang, Y Sang}
}


@misc{2014CDongCCLoyKHeXTang,
  title = {Image Super-Resolution Using Deep Convolutional Networks},
  author = {C Dong, CC Loy, K He, X Tang}
}


@misc{2014CFinnLAHendricksTDarrell,
  title = {Learning Compact Convolutional Neural Networks with Nested Dropout},
  author = {C Finn, LA Hendricks, T Darrell}
}


@misc{2014CGulcehreYBengio,
  title = {Adasecant: Robust Adaptive Secant Method for Stochastic Gradient},
  author = {C Gulcehre, Y Bengio}
}


@misc{2014CHTianYWangWTMoFCHuangWSDong,
  title = {Pre-release sales forecasting: A model-driven context feature extraction approach},
  author = {CH Tian, Y Wang, WT Mo, FC Huang, WS Dong}
}


@misc{2014CHungZXuSSukkarieh,
  title = {Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a Uav},
  author = {C Hung, Z Xu, S Sukkarieh}
}


@misc{2014CJMaddisonAHuangISutskeverDSilver,
  title = {Move Evaluation In Go Using Deep Convolutional Neural Networks},
  author = {CJ Maddison, A Huang, I Sutskever, D Silver}
}


@misc{2014CKangSLiaoYHeJWangSXiangCPan,
  title = {Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation},
  author = {C Kang, S Liao, Y He, J Wang, S Xiang, C Pan}
}


@misc{2014CKoGSohnTKRemmelJMiller,
  title = {Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data},
  author = {C Ko, G Sohn, TK Remmel, J Miller}
}


@misc{2014CLiuMTomizuka,
  title = {Control In A Safe Set: Addressing Safety In Human-robot Interactions},
  author = {C Liu, M Tomizuka}
}


@misc{2014CMayrJPartzschMNoackSHänzscheSScholze,
  title = {A Biological-Realtime Neuromorphic System in 28 nm Cmos using Low-Leakage Switched Capacitor Circuits},
  author = {C Mayr, J Partzsch, M Noack, S Hänzsche, S Scholze}
}


@misc{2014CMitchellDCordellDFam,
  title = {Beginning at the End: The outcome spaces framework to guide purposive transdisciplinary research},
  author = {C Mitchell, D Cordell, D Fam}
}


@misc{2014CPHungDCuiYChenCLinMLevine,
  title = {Correlated activity supports efficient cortical processing},
  author = {CP Hung, D Cui, Y Chen, C Lin, M Levine}
}


@misc{2014CPolancoTBuhseJACastañónGonzález,
  title = {Possible computational filter to detect proteins associated to influenza A subtype H1n1.},
  author = {C Polanco, T Buhse, JA Castañón-González}
}


@misc{2014CQinSSongGHuang,
  title = {Non-linear neighborhood component analysis based on constructive neural networks},
  author = {C Qin, S Song, G Huang}
}


@misc{2014CSabett,
  title = {Estimating Tract Variables from Acoustics via Neural Networks},
  author = {C Sabett}
}


@misc{2014CShenXHuangQZhao,
  title = {Learning of Proto-object Representations via Fixations on Low Resolution},
  author = {C Shen, X Huang, Q Zhao}
}


@misc{2014CSuiRTogneriMBennamoun,
  title = {Extracting Deep Bottleneck Features For Visual Speech Recognition},
  author = {C Sui, R Togneri, M Bennamoun}
}


@misc{2014CSzegedySReedDErhanDAnguelov,
  title = {Scalable, High-Quality Object Detection},
  author = {C Szegedy, S Reed, D Erhan, D Anguelov}
}


@misc{2014CWDengGBHuangJXuJXTang,
  title = {Extreme learning machines: new trends and applications},
  author = {CW Deng, GB Huang, J Xu, JX Tang}
}


@misc{2014CXIEYDUZGAO,
  title = {Restricted Boltzmann Machines with Svm for Object Recognition⋆},
  author = {C XIE, Y DU, Z GAO}
}


@misc{2014CXuSCetintasKCLeeLJLi,
  title = {Visual Sentiment Prediction with Deep Convolutional Neural Networks},
  author = {C Xu, S Cetintas, KC Lee, LJ Li}
}


@misc{2014CYZhangCLChen,
  title = {An automatic setting for training restricted boltzmann machine},
  author = {CY Zhang, CL Chen}
}


@misc{2014CZhangCShen,
  title = {Unsupervised Feature Learning for Dense Correspondences across Scenes},
  author = {C Zhang, C Shen}
}


@misc{2014DBalduzziHVanchinathanJBuhmann,
  title = {Kickback cuts Backprop's red-tape: Biologically plausible credit assignment in neural networks},
  author = {D Balduzzi, H Vanchinathan, J Buhmann}
}


@misc{2014DBollegalaTMaeharaYYoshidaKKawarabayashi,
  title = {Learning Word Representations from Relational Graphs},
  author = {D Bollegala, T Maehara, Y Yoshida, K Kawarabayashi}
}


@misc{2014DCMocanuGExarchakosALiotta,
  title = {Deep Learning For Objective Quality Assessment Of 3d Images},
  author = {DC Mocanu, G Exarchakos, A Liotta}
}


@misc{2014DEigenRFergus,
  title = {Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture},
  author = {D Eigen, R Fergus}
}


@misc{2014DFanYShimARaghunathanKRoy,
  title = {Stt-snn: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks},
  author = {D Fan, Y Shim, A Raghunathan, K Roy}
}


@misc{2014DGuptaRGoutamANg,
  title = {Multimedia Event Detection using Visual Features},
  author = {D Gupta, R Goutam, A Ng}
}


@misc{2014DKadetotadZXuAMohantyPYChenBLinJYe,
  title = {Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning},
  author = {D Kadetotad, Z Xu, A Mohanty, PY Chen, B Lin, J Ye}
}


@misc{2014DKotziasMDenilPBlunsomNdeFreitas,
  title = {Deep Multi-Instance Transfer Learning},
  author = {D Kotzias, M Denil, P Blunsom, N de Freitas}
}


@misc{2014DMeyer,
  title = {Can Congestion in Data Center Networks Be Predicted By Of Time Of Day?},
  author = {D Meyer}
}


@misc{2014DMeyerIntroductiontoAutoencoders,
  title = {Introduction to Autoencoders},
  author = {D Meyer}
}


@misc{2014DONikelshpur,
  title = {Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks},
  author = {DO Nikelshpur}
}


@misc{2014DPHelmboldPMLong,
  title = {On the Inductive Bias of Dropout},
  author = {DP Helmbold, PM Long}
}


@misc{2014DPalazMMDossRCollobert,
  title = {Learning linearly separable features for speech recognition using convolutional neural networks},
  author = {D Palaz, MM Doss, R Collobert}
}


@misc{2014DPathakEShelhamerJLongTDarrell,
  title = {Fully Convolutional Multi-Class Multiple Instance Learning},
  author = {D Pathak, E Shelhamer, J Long, T Darrell}
}


@misc{2014DRasmussen,
  title = {Hierarchical reinforcement learning in a biologically plausible neural architecture},
  author = {D Rasmussen}
}


@misc{2014DTranLBourdevRFergusLTorresaniMPaluri,
  title = {C3d: Generic Features for Video Analysis},
  author = {D Tran, L Bourdev, R Fergus, L Torresani, M Paluri}
}


@misc{2014DVRao,
  title = {Class Margins: Learning to (Un) Learn},
  author = {DV Rao}
}


@misc{2014DWangXTan,
  title = {C-SVDDNet: An Effective Single-Layer Network for Unsupervised Feature Learning},
  author = {D Wang, X Tan}
}


@misc{2014DWardeFarleyARabinovichDAnguelov,
  title = {Self-informed neural network structure learning},
  author = {D Warde-Farley, A Rabinovich, D Anguelov}
}


@misc{2014DXWuWPanLDXieCXHuang,
  title = {An Adaptive Stacked Denoising Auto-Encoder Architecture for Human Action Recognition},
  author = {DX Wu, W Pan, LD Xie, CX Huang}
}


@misc{2014DYAmit,
  title = {Image Recognition Using Convolutional Neural Networks},
  author = {DY Amit}
}


@misc{2014DYiZLeiSLiaoSZLi,
  title = {Learning Face Representation from Scratch},
  author = {D Yi, Z Lei, S Liao, SZ Li}
}


@misc{2014DYiZLeiSZLi,
  title = {Age Estimation by Multi-scale Convolutional Network},
  author = {D Yi, Z Lei, SZ Li}
}


@misc{2014DYuLDeng,
  title = {Recurrent Neural Networks and Related Models},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengAutomaticSpeechRecognition:,
  title = {Automatic Speech Recognition: A Deep Learning Approach},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengDeepNeuralNetwork-Hidden,
  title = {Deep Neural Network-Hidden Markov Model Hybrid Systems},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengDeepNeuralNetworks,
  title = {Deep Neural Networks},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengFeatureRepresentationLearning,
  title = {Feature Representation Learning in Deep Neural Networks},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengHiddenMarkovModels,
  title = {Hidden Markov Models and the Variants},
  author = {D Yu, L Deng}
}


@misc{2014DYuLDengRepresentationSharingand,
  title = {Representation Sharing and Transfer in Deep Neural Networks},
  author = {D Yu, L Deng}
}


@misc{2014EBarshanPFieguth,
  title = {Scalable Learning for Restricted Boltzmann Machines},
  author = {E Barshan, P Fieguth}
}


@misc{2014EBengioYWenSRuan,
  title = {Handwritten Digits Classification},
  author = {E Bengio, Y Wen, S Ruan}
}


@misc{2014ECakir,
  title = {Multilabel Sound Event Classification with Neural Networks},
  author = {E Cakir}
}


@misc{2014ECovielloGLanckriet,
  title = {Audio-based annnotatoion of video},
  author = {E Coviello, G Lanckriet}
}


@misc{2014EEtterEPaulson,
  title = {Momentum Effects on Back-Propagation Learning in a Multi-Layer Feed-Forward Neural Network},
  author = {E Etter, E Paulson}
}


@misc{2014EHofferNAilon,
  title = {Deep metric learning using Triplet network},
  author = {E Hoffer, N Ailon}
}


@misc{2014EMeedsRHendriksSFarabyMBruntinkMWelling,
  title = {MLitB: Machine Learning in the Browser},
  author = {E Meeds, R Hendriks, S Faraby, M Bruntink, M Welling}
}


@misc{2014EOyallonSMallat,
  title = {Deep Roto-Translation Scattering for Object Classification},
  author = {E Oyallon, S Mallat}
}


@misc{2014ERachmawatiISSuwardiMLKhodra,
  title = {Survey of Local Descriptor of Object Recognition System based on Rgb-d Images},
  author = {E Rachmawati, IS Suwardi, ML Khodra}
}


@misc{2014ETzengJHoffmanNZhangKSaenkoTDarrell,
  title = {Deep Domain Confusion: Maximizing for Domain Invariance},
  author = {E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell}
}


@misc{2014FAgostinelliMHoffmanPSadowskiPBaldi,
  title = {Learning Activation Functions to Improve Deep Neural Networks},
  author = {F Agostinelli, M Hoffman, P Sadowski, P Baldi}
}


@misc{2014FBisioSDecherchiPGastaldoRZunino,
  title = {Inductive Bias for Semi-supervised Extreme Learning Machine},
  author = {F Bisio, S Decherchi, P Gastaldo, R Zunino}
}


@misc{2014FFengRLiXWang,
  title = {Deep Correspondence Restricted Boltzmann Machine for Cross-modal Retrieval},
  author = {F Feng, R Li, X Wang}
}


@misc{2014FLiuCShenGLin,
  title = {Deep Convolutional Neural Fields for Depth Estimation from a Single Image},
  author = {F Liu, C Shen, G Lin}
}


@misc{2014FSrajerAGSchwingMPollefeysTPajdla,
  title = {MatchBox: Indoor Image Matching via Box-like Scene Estimation},
  author = {F Srajer, AG Schwing, M Pollefeys, T Pajdla}
}


@misc{2014GAttardiVCozzaDSartiano,
  title = {Adapting Linguistic Tools for the Analysis of Italian Medical Records},
  author = {G Attardi, V Cozza, D Sartiano}
}


@misc{2014GBRhoads,
  title = {Dermoscopic Data Acquisition Employing Display Illumination},
  author = {GB Rhoads}
}


@misc{2014GBertasiusJShiLTorresani,
  title = {DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection},
  author = {G Bertasius, J Shi, L Torresani}
}


@misc{2014GChen,
  title = {Deep Learning with Nonparametric Clustering},
  author = {G Chen}
}


@misc{2014GKutyniokMSaundersSWrightOYilmaz,
  title = {Sparse Representations, Numerical Linear Algebra, and Optimization},
  author = {G Kutyniok, M Saunders, S Wright, O Yilmaz}
}


@misc{2014GMesnilSRifaiABordesXGlorotYBengio,
  title = {Unsupervised Learning of Semantics of Object Detections for Scene Categorization},
  author = {G Mesnil, S Rifai, A Bordes, X Glorot, Y Bengio}
}


@misc{2014GMesnilYDauphinKYaoYBengioLDeng,
  title = {Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding},
  author = {G Mesnil, Y Dauphin, K Yao, Y Bengio, L Deng}
}


@misc{2014GMishneRTalmonICohen,
  title = {Graph-Based Supervised Automatic Target Detection},
  author = {G Mishne, R Talmon, I Cohen}
}


@misc{2014GMontufar,
  title = {Deep Narrow Boltzmann Machines are Universal Approximators},
  author = {G Montufar}
}


@misc{2014GMontúfarRPascanuKChoYBengio,
  title = {Supplementary Material: On the Number of Linear Regions of Deep Neural Networks},
  author = {G Montúfar, R Pascanu, K Cho, Y Bengio}
}


@misc{2014GPapandreouIKokkinosPASavalle,
  title = {Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection},
  author = {G Papandreou, I Kokkinos, PA Savalle}
}


@misc{2014HAjakanPGermainHLarochelleFLaviolette,
  title = {Domain-Adversarial Neural Networks},
  author = {H Ajakan, P Germain, H Larochelle, F Laviolette}
}


@misc{2014HAliSNTranASAGarcezTWeyde,
  title = {Convolutional Data: Towards Deep Audio Learning from Big Data},
  author = {H Ali, SN Tran, ASA Garcez, T Weyde}
}


@misc{2014HChoiHPark,
  title = {A hierarchical structure for gesture recognition using Rgb-d sensor},
  author = {H Choi, H Park}
}


@misc{2014HFGolinoCMAGomesDAndrade,
  title = {Predicting Academic Achievement of High-School Students Using Machine Learning},
  author = {HF Golino, CMA Gomes, D Andrade}
}


@misc{2014HFangSGuptaFIandolaRSrivastavaLDeng,
  title = {From Captions to Visual Concepts and Back},
  author = {H Fang, S Gupta, F Iandola, R Srivastava, L Deng}
}


@misc{2014HHamooniAMueen,
  title = {Dual-domain Hierarchical Classification of Phonetic Time Series},
  author = {H Hamooni, A Mueen}
}


@misc{2014HLiRZhaoXWang,
  title = {Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification},
  author = {H Li, R Zhao, X Wang}
}


@misc{2014HLiuBMaLQinJPangCZhangQHuang,
  title = {Set-label modeling and deep metric learning on person re-identification},
  author = {H Liu, B Ma, L Qin, J Pang, C Zhang, Q Huang}
}


@misc{2014HPanSIOlsenYZhu,
  title = {Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection},
  author = {H Pan, SI Olsen, Y Zhu}
}


@misc{2014HQiaoXXiYLiWWuFLi,
  title = {Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment},
  author = {H Qiao, X Xi, Y Li, W Wu, F Li}
}


@misc{2014HSedghiAAnandkumar,
  title = {Provable Methods for Training Neural Networks with Sparse Connectivity},
  author = {H Sedghi, A Anandkumar}
}


@misc{2014HSu,
  title = {Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations},
  author = {H Su}
}


@misc{2014HTYuFRen,
  title = {Tuta1 at the Ntcir-11 IMine Task},
  author = {HT Yu, F Ren}
}


@misc{2014HTosun,
  title = {Atomic Energy Models For Machine Learning: Atomic Restricted Boltzmann Machines},
  author = {H Tosun}
}


@misc{2014HValpola,
  title = {From neural Pca to deep unsupervised learning},
  author = {H Valpola}
}


@misc{2014HWangXShiDYYeung,
  title = {Relational Stacked Denoising Autoencoder for Tag Recommendation},
  author = {H Wang, X Shi, DY Yeung}
}


@misc{2014HYanJLuXZhou,
  title = {Prototype-Based Discriminative Feature Learning for Kinship Verification},
  author = {H Yan, J Lu, X Zhou}
}


@misc{2014HYangIPatras,
  title = {Privileged Information-based Conditional Structured Output Regression Forest for Facial Point Detection},
  author = {H Yang, I Patras}
}


@misc{2014HYinXJiaoYChaiBFang,
  title = {Scene Classification Based on Single-layer Sae and Svm},
  author = {H Yin, X Jiao, Y Chai, B Fang}
}


@misc{2014HZhaoPPoupartYZhangMLysy,
  title = {SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering},
  author = {H Zhao, P Poupart, Y Zhang, M Lysy}
}


@misc{2014HZhouJTangHZheng,
  title = {Machine Learning for Medical Applications},
  author = {H Zhou, J Tang, H Zheng}
}


@misc{2014IHJhuoDTLee,
  title = {Video Event Detection via Multi-modality Deep Learning},
  author = {IH Jhuo, DT Lee}
}


@misc{2014INwoguYZhou,
  title = {Shared features for multiple face-based biometrics},
  author = {I Nwogu, Y Zhou}
}


@misc{2014ITitovEKhoddam,
  title = {Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework},
  author = {I Titov, E Khoddam}
}


@misc{2014ITseyzer,
  title = {An Optimization of Deep Neural Networks in Asr using Singular Value Decomposition},
  author = {I Tseyzer}
}


@misc{2014JBergstraBKomerCEliasmithDWardeFarley,
  title = {Preliminary evaluation of hyperopt algorithms on HPOLib},
  author = {J Bergstra, B Komer, C Eliasmith, D Warde-Farley}
}


@misc{2014JCBanCHChang,
  title = {The Spatial Complexity of Inhomogeneous Multi-layer Neural Networks},
  author = {JC Ban, CH Chang}
}


@misc{2014JCarreiraAKarSTulsianiJMalik,
  title = {Virtual View Networks for Object Reconstruction},
  author = {J Carreira, A Kar, S Tulsiani, J Malik}
}


@misc{2014JChengDKartsaklisEGrefenstette,
  title = {Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning},
  author = {J Cheng, D Kartsaklis, E Grefenstette}
}


@misc{2014JChorowskiDBahdanauKChoYBengio,
  title = {End-to-end Continuous Speech Recognition using Attention-based Recurrent Nn: First Results},
  author = {J Chorowski, D Bahdanau, K Cho, Y Bengio}
}


@misc{2014JChungCGulcehreKHChoYBengio,
  title = {Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling},
  author = {J Chung, C Gulcehre, KH Cho, Y Bengio}
}


@misc{2014JCummer,
  title = {Methodology and Techniques for Building Modular Brain-Computer Interfaces},
  author = {J Cummer}
}


@misc{2014JDaiYNWu,
  title = {Generative Modeling of Convolutional Neural Networks},
  author = {J Dai, YN Wu}
}


@misc{2014JDonahueLAHendricksSGuadarramaMRohrbach,
  title = {Long-term Recurrent Convolutional Networks for Visual Recognition and Description},
  author = {J Donahue, LA Hendricks, S Guadarrama, M Rohrbach}
}


@misc{2014JDongSSoatto,
  title = {Domain-Size Pooling in Local Descriptors: Dsp-sift},
  author = {J Dong, S Soatto}
}


@misc{2014JEdwards,
  title = {Signal Processing in Next-Generation Prosthetics [Special Reports]},
  author = {J Edwards}
}


@misc{2014JGADolfingKMGroetheRSDixonJRBellegarda,
  title = {Multi-script Handwriting Recognition Using A Universal Recognizer},
  author = {JGA Dolfing, KM Groethe, RS Dixon, JR Bellegarda}
}


@misc{2014JGDolfingJRBellegardaUMeierRDixon,
  title = {Real-time Stroke-order And Stroke-direction Independent Handwriting Recognition},
  author = {JG Dolfing, JR Bellegarda, U Meier, R Dixon}
}


@misc{2014JHanDZhangXHuLGuoJRenFWu,
  title = {Background Prior Based Salient Object Detection via Deep Reconstruction Residual},
  author = {J Han, D Zhang, X Hu, L Guo, J Ren, F Wu}
}


@misc{2014JHelmsen,
  title = {Systems and methods for analyzing data using deep belief networks (dbn) and identifying a pattern in a graph},
  author = {J Helmsen}
}


@misc{2014JHoffmanDPathakTDarrellKSaenko,
  title = {Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning},
  author = {J Hoffman, D Pathak, T Darrell, K Saenko}
}


@misc{2014JJinADundarECulurciello,
  title = {Flattened Convolutional Neural Networks for Feedforward Acceleration},
  author = {J Jin, A Dundar, E Culurciello}
}


@misc{2014JKChenZChenZChiHFu,
  title = {Emotion Recognition in the Wild with Feature Fusion and Multiple Kernel Learning},
  author = {JK Chen, Z Chen, Z Chi, H Fu}
}


@misc{2014JLehmanJCluneSRisi,
  title = {An Anarchy of Methods: Current Trends in How Intelligence Is Abstracted in Ai},
  author = {J Lehman, J Clune, S Risi}
}


@misc{2014JLi,
  title = {Feature Weight Tuning for Recursive Neural Networks},
  author = {J Li}
}


@misc{2014JLiHChangJYang,
  title = {Sparse Deep Stacking Network for Image Classification},
  author = {J Li, H Chang, J Yang}
}


@misc{2014JLongEShelhamerTDarrell,
  title = {Fully Convolutional Networks for Semantic Segmentation},
  author = {J Long, E Shelhamer, T Darrell}
}


@misc{2014JMBae,
  title = {Clinical Decision Analysis using Decision Tree},
  author = {JM Bae}
}


@misc{2014JMairalFBachJPonce,
  title = {Foundations and Trends® in Computer Graphics and Vision},
  author = {J Mairal, F Bach, J Ponce}
}


@misc{2014JMartinezHHHoosJJLittle,
  title = {Stacked Quantizers for Compositional Vector Compression},
  author = {J Martinez, HH Hoos, JJ Little}
}


@misc{2014JRedmonAAngelova,
  title = {Real-Time Grasp Detection Using Convolutional Neural Networks},
  author = {J Redmon, A Angelova}
}


@misc{2014JRudyWDingDJImGWTaylor,
  title = {Neural Network Regularization via Robust Weight Factorization},
  author = {J Rudy, W Ding, DJ Im, GW Taylor}
}


@misc{2014JShenMLee,
  title = {Implementation of discriminative and generative deep learning},
  author = {J Shen, M Lee}
}


@misc{2014JTHLoYGuiYPeng,
  title = {The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks},
  author = {JTH Lo, Y Gui, Y Peng}
}


@misc{2014JTSpringenbergADosovitskiyTBroxMRiedmiller,
  title = {Striving for Simplicity: The All Convolutional Net},
  author = {JT Springenberg, A Dosovitskiy, T Brox, M Riedmiller}
}


@misc{2014JTompsonRGoroshinAJainYLeCunCBregler,
  title = {Efficient Object Localization Using Convolutional Networks},
  author = {J Tompson, R Goroshin, A Jain, Y LeCun, C Bregler}
}


@misc{2014JWangZDengSWangQGao,
  title = {Training Generalized Feedforword Kernelized Neural Networks on Very Large Datasets for Regression Using Minimal-Enclosing-Ball Approximation},
  author = {J Wang, Z Deng, S Wang, Q Gao}
}


@misc{2014JXuHLiSZhou,
  title = {An Overview of Deep Generative Models},
  author = {J Xu, H Li, S Zhou}
}


@misc{2014JYangYSunLZhangQZhang,
  title = {Robust Multi-Layer Hierarchical Model for Digit Character Recognition},
  author = {J Yang, Y Sun, L Zhang, Q Zhang}
}


@misc{2014JYosinskiJCluneYBengioHLipson,
  title = {How transferable are features in deep neural networks?},
  author = {J Yosinski, J Clune, Y Bengio, H Lipson}
}


@misc{2014JZhangMKanSShanXZhaoXChen,
  title = {Topic-aware Deep Auto-encoders (tda) for Face Alignment},
  author = {J Zhang, M Kan, S Shan, X Zhao, X Chen}
}


@misc{2014KBISWARANJANSSARKARDRASETHI,
  title = {Diagnosis Of Diabetic Retinopathy By Segmentation Of Blood Vessels In Retinal Images},
  author = {K BISWARANJAN, S SARKAR, DRA SETHI}
}


@misc{2014KChalupkaPPeronaFEberhardt,
  title = {Visual Causal Feature Learning},
  author = {K Chalupka, P Perona, F Eberhardt}
}


@misc{2014KChangCChen,
  title = {A Learning Framework for Age Rank Estimation based on Face Images with Scattering Transform},
  author = {K Chang, C Chen}
}


@misc{2014KEggenspergerFHutterHHHoosKLeytonBrown,
  title = {Efficient Benchmarking of Hyperparameter Optimizers via Surrogates},
  author = {K Eggensperger, F Hutter, HH Hoos, K Leyton-Brown}
}


@misc{2014KFragkiadakiPArbelaezPFelsenJMalik,
  title = {Spatio-Temporal Moving Object Proposals},
  author = {K Fragkiadaki, P Arbelaez, P Felsen, J Malik}
}


@misc{2014KGoelRVohra,
  title = {Learning Temporal Dependencies in Data Using a Dbn-blstm},
  author = {K Goel, R Vohra}
}


@misc{2014KHan,
  title = {Supervised Speech Separation And Processing},
  author = {K Han}
}


@misc{2014KHeJSun,
  title = {Convolutional Neural Networks at Constrained Time Cost},
  author = {K He, J Sun}
}


@misc{2014KHwangWSung,
  title = {Fixed-point feedforward deep neural network design using weights+ 1, 0, and− 1},
  author = {K Hwang, W Sung}
}


@misc{2014KINTEKNG,
  title = {A Distributed Implementation of Training the Restricted Boltzmann Machine},
  author = {KINTEK NG}
}


@misc{2014KKangXWang,
  title = {Fully Convolutional Neural Networks for Crowd Segmentation},
  author = {K Kang, X Wang}
}


@misc{2014KKim,
  title = {Emotion Modeling and Machine Learning in Affective Computing},
  author = {K Kim}
}


@misc{2014KLencAVedaldi,
  title = {Understanding image representations by measuring their equivariance and equivalence},
  author = {K Lenc, A Vedaldi}
}


@misc{2014KNodaYYamaguchiKNakadaiHGOkunoTOgata,
  title = {Audio-visual speech recognition using deep learning},
  author = {K Noda, Y Yamaguchi, K Nakadai, HG Okuno, T Ogata}
}


@misc{2014KRohanimanesh,
  title = {An Information Theoretic Approach to Quantifying Text Interestingness},
  author = {K Rohanimanesh}
}


@misc{2014KSTaiSXu,
  title = {Distributed Training of Neural Network Language Models},
  author = {KS Tai, S Xu}
}


@misc{2014LBazzaniABergamoDAnguelovLTorresani,
  title = {Self-Taught Object Localization with Deep Networks},
  author = {L Bazzani, A Bergamo, D Anguelov, L Torresani}
}


@misc{2014LCChenGPapandreouIKokkinosKMurphy,
  title = {Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs},
  author = {LC Chen, G Papandreou, I Kokkinos, K Murphy}
}


@misc{2014LCaoCWang,
  title = {Practice in Synonym Extraction at Large Scale},
  author = {L Cao, C Wang}
}


@misc{2014LGHafemann,
  title = {An analysis of deep neural networks for texture classification},
  author = {LG Hafemann}
}


@misc{2014LGuoSLiXNiuYDou,
  title = {A Study on Layer Connection Strategies in Stacked Convolutional Deep Belief Networks},
  author = {L Guo, S Li, X Niu, Y Dou}
}


@misc{2014LPeiMYeXZhaoTXiangTLi,
  title = {Learning spatio-temporal features for action recognition from the side of the video},
  author = {L Pei, M Ye, X Zhao, T Xiang, T Li}
}


@misc{2014LShenGSunSWangEWuQHuang,
  title = {Sharing Model With Multi-level Feature Representations},
  author = {L Shen, G Sun, S Wang, E Wu, Q Huang}
}


@misc{2014LXueFSu,
  title = {Auditory Scene Classification with Deep Belief Network},
  author = {L Xue, F Su}
}


@misc{2014LYuKMHermannPBlunsomSPulman,
  title = {Deep Learning for Answer Sentence Selection},
  author = {L Yu, KM Hermann, P Blunsom, S Pulman}
}


@misc{2014LZhangTYangRJinZHZhou,
  title = {Online Bandit Learning for a Special Class of Non-convex Losses},
  author = {L Zhang, T Yang, R Jin, ZH Zhou}
}


@misc{2014LZhaoKJia,
  title = {Deep Adaptive Log-Demons–Diffeomorphic Image Registration with Very Large Deformations},
  author = {L Zhao, K Jia}
}


@misc{2014MAKeyvanradMMHomayounpour,
  title = {Deep Belief Network Training Improvement Using Elite Samples Minimizing Free Energy},
  author = {MA Keyvanrad, MM Homayounpour}
}


@misc{2014MBlaschko,
  title = {Advances in Empirical Risk Minimization for Image Analysis and Pattern Recognition},
  author = {M Blaschko}
}


@misc{2014MCimpoiSMajiAVedaldi,
  title = {Deep convolutional filter banks for texture recognition and segmentation},
  author = {M Cimpoi, S Maji, A Vedaldi}
}


@misc{2014MCogswellXLinSPurushwalkamDBatra,
  title = {Combining the Best of Graphical Models and ConvNets for Semantic Segmentation},
  author = {M Cogswell, X Lin, S Purushwalkam, D Batra}
}


@misc{2014MCourbariauxYBengioJPDavid,
  title = {Low precision arithmetic for deep learning},
  author = {M Courbariaux, Y Bengio, JP David}
}


@misc{2014MDCollinsPKohli,
  title = {Memory Bounded Deep Convolutional Networks},
  author = {MD Collins, P Kohli}
}


@misc{2014MDMcDonnellMDTisseraAvanSchaikJTapson,
  title = {Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights},
  author = {MD McDonnell, MD Tissera, A van Schaik, J Tapson}
}


@misc{2014MGieringKReddyVVenugopalan,
  title = {Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks},
  author = {M Giering, K Reddy, V Venugopalan}
}


@misc{2014MHarandiMSalzmann,
  title = {Riemannian Coding and Dictionary Learning: Kernels to the Rescue},
  author = {M Harandi, M Salzmann}
}


@misc{2014MJSkwarkDRaimondiMMichelAElofsson,
  title = {Improved contact predictions using the recognition of protein like contact patterns.},
  author = {MJ Skwark, D Raimondi, M Michel, A Elofsson}
}


@misc{2014MJaderbergKSimonyanAVedaldiAZisserman,
  title = {Reading Text in the Wild with Convolutional Neural Networks},
  author = {M Jaderberg, K Simonyan, A Vedaldi, A Zisserman}
}


@misc{2014MJaderbergKSimonyanAVedaldiAZissermanDeepStructuredOutput,
  title = {Deep Structured Output Learning for Unconstrained Text Recognition},
  author = {M Jaderberg, K Simonyan, A Vedaldi, A Zisserman}
}


@misc{2014MJanzaminHSedghiAAnandkumar,
  title = {Matrix and Tensor Features for Discriminative Learning},
  author = {M Janzamin, H Sedghi, A Anandkumar}
}


@misc{2014MJanzaminHSedghiAAnandkumarScoreFunctionFeatures,
  title = {Score Function Features for Discriminative Learning},
  author = {M Janzamin, H Sedghi, A Anandkumar}
}


@misc{2014MKarthickSUmesh,
  title = {Improving Deep Neural Networks Using State Projection Vectors Of Subspace Gaussian Mixture Model As Features},
  author = {M Karthick, S Umesh}
}


@misc{2014MKiefelVJampaniPVGehler,
  title = {Permutohedral Lattice CNNs},
  author = {M Kiefel, V Jampani, PV Gehler}
}


@misc{2014MKlećDKoržinek,
  title = {Unsupervised Feature Pre-training of the Scattering Wavelet Transform for Musical Genre Recognition},
  author = {M Kleć, D Koržinek}
}


@misc{2014MKorpusikNSchmidtJDrexlerSCyphersJGlass,
  title = {Data collection and language understanding of food descriptions},
  author = {M Korpusik, N Schmidt, J Drexler, S Cyphers, J Glass}
}


@misc{2014MKoutsombogeraHPapageorgiou,
  title = {Multimodal Analytics and its Data Ecosystem},
  author = {M Koutsombogera, H Papageorgiou}
}


@misc{2014MKächeleMGlodekDZharkovSMeudt,
  title = {Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression},
  author = {M Kächele, M Glodek, D Zharkov, S Meudt}
}


@misc{2014MLeordeanuARaduRSukthankar,
  title = {Features in Concert: Discriminative Feature Selection meets Unsupervised Clustering},
  author = {M Leordeanu, A Radu, R Sukthankar}
}


@misc{2014MLiangZLiTChenJZeng,
  title = {Integrative Data Analysis of Multi-platform Cancer Data with a Multimodal Deep Learning Approach},
  author = {M Liang, Z Li, T Chen, J Zeng}
}


@misc{2014MLinSLiXLuoSYan,
  title = {Purine: A bi-graph based deep learning framework},
  author = {M Lin, S Li, X Luo, S Yan}
}


@misc{2014MLängkvistALoutfi,
  title = {Learning Feature Representations with a Cost-Relevant Sparse Autoencoder},
  author = {M Längkvist, A Loutfi}
}


@misc{2014MMirzaSOsindero,
  title = {Conditional Generative Adversarial Nets},
  author = {M Mirza, S Osindero}
}


@misc{2014MOginoTShibaharaYNoguchiTTsujita,
  title = {High-definition 3d Image Processing Technology for Ultrasound Diagnostic Scanners},
  author = {M Ogino, T Shibahara, Y Noguchi, T Tsujita}
}


@misc{2014MProbstFRothlaufJGrahl,
  title = {Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization},
  author = {M Probst, F Rothlauf, J Grahl}
}


@misc{2014MRFerrier,
  title = {Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function},
  author = {MR Ferrier}
}


@misc{2014MSahasrabudheAMNamboodiri,
  title = {Fingerprint Enhancement Using Unsupervised Hierarchical Feature Learning},
  author = {M Sahasrabudhe, AM Namboodiri}
}


@misc{2014MSajjadiMSeyedhosseiniTTasdizen,
  title = {Disjunctive Normal Networks},
  author = {M Sajjadi, M Seyedhosseini, T Tasdizen}
}


@misc{2014MSchoelerFWörgötterJPaponTKulvicius,
  title = {Unsupervised generation of context-relevant training-sets for visual object recognition employing multilinguality},
  author = {M Schoeler, F Wörgötter, J Papon, T Kulvicius}
}


@misc{2014MSchuldISinayskiyFPetruccione,
  title = {Simulating a perceptron on a quantum computer},
  author = {M Schuld, I Sinayskiy, F Petruccione}
}


@misc{2014MSongTChambers,
  title = {Text Mining with the Stanford CoreNLP},
  author = {M Song, T Chambers}
}


@misc{2014MThulinPMasek,
  title = {Software Quality Evaluation of Face Recognition APIs & Libraries},
  author = {M Thulin, P Masek}
}


@misc{2014MUedaYNishitaniYKanekoAOmote,
  title = {Back-Propagation Operation for Analog Neural Network Hardware with Synapse Components Having Hysteresis Characteristics},
  author = {M Ueda, Y Nishitani, Y Kaneko, A Omote}
}


@misc{2014MXiaJGDolfingRSDixonKMGroetheKMisra,
  title = {Managing Real-time Handwriting Recognition},
  author = {M Xia, JG Dolfing, RS Dixon, KM Groethe, K Misra}
}


@misc{2014MZhaoCZhuangYWangTSLee,
  title = {Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction},
  author = {M Zhao, C Zhuang, Y Wang, TS Lee}
}


@misc{2014NDLanePGeorgiev,
  title = {Can Deep Learning Revolutionize Mobile Sensing?},
  author = {ND Lane, P Georgiev}
}


@misc{2014NGALAYOUSS,
  title = {A critical examination of deep learning approaches to automated speech recognition},
  author = {NGA LAYOUSS}
}


@misc{2014NItenDPetko,
  title = {Learning with serious games: is fun playing the game a predictor of learning success?},
  author = {N Iten, D Petko}
}


@misc{2014NKrügerMZillichPJanssenAGBuch,
  title = {What We Can Learn From the Primate's Visual System},
  author = {N Krüger, M Zillich, P Janssen, AG Buch}
}


@misc{2014NMohajerinSLWaslander,
  title = {Modular deep Recurrent Neural Network: Application to quadrotors},
  author = {N Mohajerin, SL Waslander}
}


@misc{2014NNeverovaCWolfGWTaylorFNebout,
  title = {ModDrop: adaptive multi-modal gesture recognition},
  author = {N Neverova, C Wolf, GW Taylor, F Nebout}
}


@misc{2014NTripathiAJadeja,
  title = {A Survey of Regularization Methods for Deep Neural Network},
  author = {N Tripathi, A Jadeja}
}


@misc{2014NWiebeAKapoorKMSvore,
  title = {Quantum Deep Learning},
  author = {N Wiebe, A Kapoor, KM Svore}
}


@misc{2014OFiratEAksanIOztekinFTYVural,
  title = {Learning Deep Temporal Representations for Brain Decoding},
  author = {O Firat, E Aksan, I Oztekin, FTY Vural}
}


@misc{2014OIrsoyCCardie,
  title = {Deep Recursive Neural Networks for Compositionality in Language},
  author = {O Irsoy, C Cardie}
}


@misc{2014OIsayevDFourchesENMuratovCOsesKRasch,
  title = {Large Materials Cartography: Representing and Mining Material Space Using Structural and Electronic Fingerprints},
  author = {O Isayev, D Fourches, EN Muratov, C Oses, K Rasch}
}


@misc{2014OVinyalsAToshevSBengioDErhan,
  title = {Show and Tell: A Neural Image Caption Generator},
  author = {O Vinyals, A Toshev, S Bengio, D Erhan}
}


@misc{2014PAgrawal,
  title = {Analysis of Multilayer Neural Networks for Object Recognition},
  author = {P Agrawal}
}


@misc{2014PBezakPBozekYNikitin,
  title = {Advanced Robotic Grasping System Using Deep Learning},
  author = {P Bezak, P Bozek, Y Nikitin}
}


@misc{2014PBezákYRNikitinPBožek,
  title = {Robotic Grasping System Using Convolutional Neural Networks},
  author = {P Bezák, YR Nikitin, P Božek}
}


@misc{2014PDARSMZdenek,
  title = {Comparative Study Of Machine Learning Techniques For Supervised Classification Of Biomedical Data},
  author = {PD AR, SM Zdenek}
}


@misc{2014PHála,
  title = {Spectral classification using convolutional neural networks},
  author = {P Hála}
}


@misc{2014PRAFirminoPSGdeMattosNetoTAEFerreira,
  title = {Error Modeling Approach to Improve Time Series Forecasters},
  author = {PRA Firmino, PSG de Mattos Neto, TAE Ferreira}
}


@misc{2014PSprechmannAMBronsteinGSapiro,
  title = {Supervised non-negative matrix factorization for audio source separation},
  author = {P Sprechmann, AM Bronstein, G Sapiro}
}


@misc{2014PXieMBilenkoTFinleyRGiladBachrachKLauter,
  title = {Crypto-nets: Neural Networks Over En-crypted Data},
  author = {P Xie, M Bilenko, T Finley, R Gilad-Bachrach, K Lauter}
}


@misc{2014PZhangSLiYZhou,
  title = {An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application},
  author = {P Zhang, S Li, Y Zhou}
}


@misc{2014QQiuGSapiroABronstein,
  title = {Random Forests Can Hash},
  author = {Q Qiu, G Sapiro, A Bronstein}
}


@misc{2014QWangYWangZWang,
  title = {Online Smart Face Morphing Engine with Prior Constraints and Local Geometry Preservation},
  author = {Q Wang, Y Wang, Z Wang}
}


@misc{2014RCYuanHYanXMZhouFCDiLXLi,
  title = {Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology},
  author = {RC Yuan, H Yan, XM Zhou, FC Di, LX Li}
}


@misc{2014RDingBZhaoSChen,
  title = {A neuromorphic categorization system with Online Sequential Extreme Learning},
  author = {R Ding, B Zhao, S Chen}
}


@misc{2014RFernandezARendel,
  title = {Hybrid Predictive Model For Enhancing Prosodic Expressiveness},
  author = {R Fernandez, A Rendel}
}


@misc{2014RFrassettoNogueiraRdeAlencarLotufo,
  title = {Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns},
  author = {R Frassetto Nogueira, R de Alencar Lotufo}
}


@misc{2014RGhoshAMishraGOrchardNVThakor,
  title = {Real-time object recognition and orientation estimation using an event-based camera and Cnn},
  author = {R Ghosh, A Mishra, G Orchard, NV Thakor}
}


@misc{2014RGiryesGSapiroAMBronstein,
  title = {On the Stability of Deep Networks},
  author = {R Giryes, G Sapiro, AM Bronstein}
}


@misc{2014RGoroshinJBrunaJTompsonDEigenYLeCun,
  title = {Unsupervised Learning of Spatiotemporally Coherent Metrics},
  author = {R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun}
}


@misc{2014RHeMZhangLWangYJiQYin,
  title = {Cross-Modal Learning via Pairwise Constraints},
  author = {R He, M Zhang, L Wang, Y Ji, Q Yin}
}


@misc{2014RJKannanSSubramanian,
  title = {An Adaptive Approach of Tamil Character Recognition Using Deep Learning with Big Data-A Survey},
  author = {RJ Kannan, S Subramanian}
}


@misc{2014RJohnsonTZhang,
  title = {Effective Use of Word Order for Text Categorization with Convolutional Neural Networks},
  author = {R Johnson, T Zhang}
}


@misc{2014RKirosRSalakhutdinovRSZemel,
  title = {Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models},
  author = {R Kiros, R Salakhutdinov, RS Zemel}
}


@misc{2014RKumarRKSharmaASharma,
  title = {Recognition of Multi-Stroke Based Online Handwritten Gurmukhi Aksharas},
  author = {R Kumar, RK Sharma, A Sharma}
}


@misc{2014RLiFFengXWangPLuBLi,
  title = {Obtaining Cross-modal Similarity Metric with Deep Neural Architecture},
  author = {R Li, F Feng, X Wang, P Lu, B Li}
}


@misc{2014RMCCOPPIN,
  title = {An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines},
  author = {R MCCOPPIN}
}


@misc{2014RMGolden,
  title = {Stochastic Descent Analysis of Representation Learning Algorithms},
  author = {RM Golden}
}


@misc{2014RMKeller,
  title = {Machine Learning Applied to Musical Improvisation},
  author = {RM Keller}
}


@misc{2014RMohan,
  title = {Deep Deconvolutional Networks for Scene Parsing},
  author = {R Mohan}
}


@misc{2014RRanganathLTangLCharlinDMBlei,
  title = {Deep Exponential Families},
  author = {R Ranganath, L Tang, L Charlin, DM Blei}
}


@misc{2014RSDixonJGDolfingUMeierJRBellegarda,
  title = {Integrating Stroke-distribution Information Into Spatial Feature Extraction For Automatic Handwriting Recognition},
  author = {RS Dixon, JG Dolfing, U Meier, JR Bellegarda}
}


@misc{2014RSerizelDGiuliani,
  title = {Vocal Tract Length Normalisation Approaches To Dnn-based Children's And Adults'speech Recognition},
  author = {R Serizel, D Giuliani}
}


@misc{2014RSerizelDGiulianiFBKFBK,
  title = {Deep neural network adaptation for children's and adults' speech recognition},
  author = {R Serizel, D Giuliani, FBK FBK}
}


@misc{2014RVedantamCLZitnickDParikh,
  title = {CIDEr: Consensus-based Image Description Evaluation},
  author = {R Vedantam, CL Zitnick, D Parikh}
}


@misc{2014RYangSGeKXieSChen,
  title = {Eye Localization Based on Multi-Channel Correlation Filter Bank},
  author = {R Yang, S Ge, K Xie, S Chen}
}


@misc{2014RZengJWuZShaoLSenhadjiHShu,
  title = {Quaternion softmax classifier},
  author = {R Zeng, J Wu, Z Shao, L Senhadji, H Shu}
}


@misc{2014SAfsharLGeorgeJTapsonAvanSchaik,
  title = {Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels},
  author = {S Afshar, L George, J Tapson, A van Schaik}
}


@misc{2014SChatzis,
  title = {A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis},
  author = {S Chatzis}
}


@misc{2014SDSarmaMFreedmanCNayak,
  title = {Majorana Zero Modes and Topological Quantum Computation},
  author = {SD Sarma, M Freedman, C Nayak}
}


@misc{2014SDingNZhangXXuLGuoJZhang,
  title = {Deep Extreme Learning Machine and Its Application in Eeg Classification},
  author = {S Ding, N Zhang, X Xu, L Guo, J Zhang}
}


@misc{2014SFerrerTRuiz,
  title = {Travel Behavior Characterization Using Raw Accelerometer Data Collected from Smartphones},
  author = {S Ferrer, T Ruiz}
}


@misc{2014SFeyzabadi,
  title = {Joint Deep Learning for Car Detection},
  author = {S Feyzabadi}
}


@misc{2014SGaoLDuanITsang,
  title = {DEFEATnet--A Deep Conventional Image Representation for Image Classification},
  author = {S Gao, L Duan, I Tsang}
}


@misc{2014SGoyalPBenjamin,
  title = {Object Recognition Using Deep Neural Networks: A Survey},
  author = {S Goyal, P Benjamin}
}


@misc{2014SGuLRigazio,
  title = {Towards Deep Neural Network Architectures Robust to Adversarial Examples},
  author = {S Gu, L Rigazio}
}


@misc{2014SHussainSCLiuABasu,
  title = {Hardware-Amenable Structural Learning for Spike-based Pattern Classification using a Simple Model of Active Dendrites},
  author = {S Hussain, SC Liu, A Basu}
}


@misc{2014SKhorramHSametiSKing,
  title = {Soft context clustering for F0 modeling in HMM-based speech synthesis},
  author = {S Khorram, H Sameti, S King}
}


@misc{2014SMoonSKimHWang,
  title = {Multimodal Transfer Deep Learning for Audio Visual Recognition},
  author = {S Moon, S Kim, H Wang}
}


@misc{2014SNieZWangQJi,
  title = {A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling},
  author = {S Nie, Z Wang, Q Ji}
}


@misc{2014SQiFWangXWangYGuanJWeiJGuan,
  title = {Multiple level visual semantic fusion method for image re-ranking},
  author = {S Qi, F Wang, X Wang, Y Guan, J Wei, J Guan}
}


@misc{2014SReedHLeeDAnguelovCSzegedyDErhan,
  title = {Training Deep Neural Networks on Noisy Labels with Bootstrapping},
  author = {S Reed, H Lee, D Anguelov, C Szegedy, D Erhan}
}


@misc{2014SSTirumala,
  title = {Implementation of Evolutionary Algorithms for Deep Architectures},
  author = {SS Tirumala}
}


@misc{2014SSalehiASelamatRMasinchiHFujita,
  title = {The Synergistic Combination of Particle Swarm Optimization and Fuzzy Sets to Design Granular Classifier},
  author = {S Salehi, A Selamat, R Masinchi, H Fujita}
}


@misc{2014SSarkarVVenugopalanKReddyMGieringJRyde,
  title = {Occlusion Edge Detection in Rgb-d Frames using Deep Convolutional Networks},
  author = {S Sarkar, V Venugopalan, K Reddy, M Giering, J Ryde}
}


@misc{2014SShalevShwartz,
  title = {SelfieBoost: A Boosting Algorithm for Deep Learning},
  author = {S Shalev-Shwartz}
}


@misc{2014SSickertERodnerJDenzler,
  title = {Semantic Volume Segmentation with Iterative Context Integration},
  author = {S Sickert, E Rodner, J Denzler}
}


@misc{2014SSoatto,
  title = {Visual Scene Representations: Sufficiency, Minimality, Invariance and Approximations},
  author = {S Soatto}
}


@misc{2014SSoattoJDongNKarianakis,
  title = {Visual Scene Representations: Scaling and Occlusion in Convolutional Architectures},
  author = {S Soatto, J Dong, N Karianakis}
}


@misc{2014SThomasCChatelainLHeutteTPaquet,
  title = {A deep Hmm model for multiple keywords spotting in handwritten documents},
  author = {S Thomas, C Chatelain, L Heutte, T Paquet}
}


@misc{2014STuYXueJWangXHuangXZhang,
  title = {Learning Block Group Sparse Representation Combined with Convolutional Neural Networks for Rgb-d Object Recognition},
  author = {S Tu, Y Xue, J Wang, X Huang, X Zhang}
}


@misc{2014SVenugopalanHXuJDonahueMRohrbach,
  title = {Translating Videos to Natural Language Using Deep Recurrent Neural Networks},
  author = {S Venugopalan, H Xu, J Donahue, M Rohrbach}
}


@misc{2014SWoźniakADAlmásiVCristeaYLeblebici,
  title = {Review of Advances in Neural Networks: Neural Design Technology Stack},
  author = {S Woźniak, AD Almási, V Cristea, Y Leblebici}
}


@misc{2014SXuXMeiWDongXSunXShenXZhang,
  title = {Depth of field rendering via adaptive recursive filtering},
  author = {S Xu, X Mei, W Dong, X Sun, X Shen, X Zhang}
}


@misc{2014SXueOAbdelHamidHJiangLDaiQLiu,
  title = {Fast adaptation of deep neural network based on discriminant codes for speech recognition},
  author = {S Xue, O Abdel-Hamid, H Jiang, L Dai, Q Liu}
}


@misc{2014SYangPLuoCCLoyKWShumXTang,
  title = {Deep Representation Learning with Target Coding},
  author = {S Yang, P Luo, CC Loy, KW Shum, X Tang}
}


@misc{2014SYangPLuoCCLoyKWShumXTangDeepRepresentationLearning,
  title = {Deep Representation Learning with Target Coding Supplementary Material},
  author = {S Yang, P Luo, CC Loy, KW Shum, X Tang}
}


@misc{2014SZhangAChoromanskaYLeCun,
  title = {Deep learning with Elastic Averaging Sgd},
  author = {S Zhang, A Choromanska, Y LeCun}
}


@misc{2014SZhangKKang,
  title = {Learning High-level Features by Deep Boltzmann Machines for Handwriting Digits Recogintion},
  author = {S Zhang, K Kang}
}


@misc{2014SZhaoHYaoSZhaoXJiangXJiang,
  title = {Multi-modal microblog classification via multi-task learning},
  author = {S Zhao, H Yao, S Zhao, X Jiang, X Jiang}
}


@misc{2014TAOYANGXZHAOBLINTAOZENGSJIJYE,
  title = {Automated Gene Expression Pattern Annotation In The Mouse Brain},
  author = {TAO YANG, X ZHAO, B LIN, TAO ZENG, S JI, J YE}
}


@misc{2014TAdams,
  title = {Brain Edge Detection},
  author = {T Adams}
}


@misc{2014TBroschRTam,
  title = {Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2d and 3d Images},
  author = {T Brosch, R Tam}
}


@misc{2014THassnerSHarelEPazREnbar,
  title = {Effective Face Frontalization in Unconstrained Images},
  author = {T Hassner, S Harel, E Paz, R Enbar}
}


@misc{2014THoritaITakanamiMAkibaMTerauchiTKanno,
  title = {A GPGPU-Based Acceleration of Fault-Tolerant Mlp Learnings},
  author = {T Horita, I Takanami, M Akiba, M Terauchi, T Kanno}
}


@misc{2014TKoriyamaTNoseTKobayashi,
  title = {Parametric Speech Synthesis Using Local and Global Sparse Gaussian},
  author = {T Koriyama, T Nose, T Kobayashi}
}


@misc{2014TLPainePKhorramiWHanTSHuang,
  title = {An Analysis of Unsupervised Pre-training in Light of Recent Advances},
  author = {TL Paine, P Khorrami, W Han, TS Huang}
}


@misc{2014TLiuMLi,
  title = {Improving relation descriptor extraction with word embeddings and cluster features},
  author = {T Liu, M Li}
}


@misc{2014TNakashikaTTakiguchiYAriki,
  title = {Voice Conversion Using Rnn Pre-Trained by Recurrent Temporal Restricted Boltzmann Machines},
  author = {T Nakashika, T Takiguchi, Y Ariki}
}


@misc{2014TUnterthinerAMayrGKlambauerMSteijaert,
  title = {Multi-Task Deep Networks for Drug Target Prediction},
  author = {T Unterthiner, A Mayr, G Klambauer, M Steijaert}
}


@misc{2014TVNguyenCLuJSepulvedaSYan,
  title = {Adaptive Nonparametric Image Parsing},
  author = {TV Nguyen, C Lu, J Sepulveda, S Yan}
}


@misc{2014TXiaoYXuKYangJZhangYPengZZhang,
  title = {The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification},
  author = {T Xiao, Y Xu, K Yang, J Zhang, Y Peng, Z Zhang}
}


@misc{2014TYDuJunXYongLCHDaiLirong,
  title = {Speech Separation of A Target Speaker Based on Deep Neural Networks},
  author = {TY Du Jun, X Yong, LCH Dai Lirong}
}


@misc{2014TYanhuiDJunXYongDLirongLChinHui,
  title = {Deep Neural Network Based Speech Separation for Robust Speech Recognition},
  author = {T Yanhui, D Jun, X Yong, D Lirong, L Chin-Hui}
}


@misc{2014TYoshiokaMJFGales,
  title = {Environmentally robust Asr front-end for deep neural network acoustic models},
  author = {T Yoshioka, MJF Gales}
}


@misc{2014USümbülAZlateskiAVishwanathanRHMasland,
  title = {Automated computation of arbor densities: a step toward identifying neuronal cell types},
  author = {U Sümbül, A Zlateski, A Vishwanathan, RH Masland}
}


@misc{2014VDLuongLWangGXiao,
  title = {Action Recognition Using Hierarchical Independent Subspace Analysis with Trajectory},
  author = {VD Luong, L Wang, G Xiao}
}


@misc{2014WAdamsKPlis,
  title = {Energy Based Models and Boltzmann Machines (Cont.)},
  author = {W Adams, K Plis}
}


@misc{2014WChenGGuo,
  title = {TriViews: A general framework to use 3d depth data effectively for action recognition},
  author = {W Chen, G Guo}
}


@misc{2014WDingRWangFMaoGTaylor,
  title = {Theano-based Large-Scale Visual Recognition with Multiple GPUs},
  author = {W Ding, R Wang, F Mao, G Taylor}
}


@misc{2014WHLeleCaoFSun,
  title = {A Deep and Stable Extreme Learning Approach for Classification and Regression⋆},
  author = {WH Le-le Cao, F Sun}
}


@misc{2014WHuYQianFKSoongYWang,
  title = {Improved Mispronunciation Detection with Deep Neural Network Trained Acoustic Models and Transfer Learning based Logistic Regression Classifiers},
  author = {W Hu, Y Qian, FK Soong, Y Wang}
}


@misc{2014WHuangFSun,
  title = {A Deep and Stable Extreme Learning Approach for Classification and Regression},
  author = {W Huang, F Sun}
}


@misc{2014WOuyangXWangXZengSQiuPLuoYTianHLi,
  title = {DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection},
  author = {W Ouyang, X Wang, X Zeng, S Qiu, P Luo, Y Tian, H Li}
}


@misc{2014WSongWXuLLiuHWang,
  title = {Cnu System in Ntcir-11 IMine Task},
  author = {W Song, W Xu, L Liu, H Wang}
}


@misc{2014WZhangRLiHDengLWangWLinSJiDShen,
  title = {Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation},
  author = {W Zhang, R Li, H Deng, L Wang, W Lin, S Ji, D Shen}
}


@misc{2014XChangFNieZMaYYangXZhou,
  title = {A Convex Formulation for Spectral Shrunk Clustering},
  author = {X Chang, F Nie, Z Ma, Y Yang, X Zhou}
}


@misc{2014XChenAYuille,
  title = {Parsing Occluded People by Flexible Compositions},
  author = {X Chen, A Yuille}
}


@misc{2014XChenXChengSMallat,
  title = {Unsupervised Deep Haar Scattering on Graphs},
  author = {X Chen, X Cheng, S Mallat}
}


@misc{2014XLZhang,
  title = {Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?},
  author = {XL Zhang}
}


@misc{2014XLiuKDuhYMatsumotoTIwakura,
  title = {Learning Character Representations for Chinese Word Segmentation},
  author = {X Liu, K Duh, Y Matsumoto, T Iwakura}
}


@misc{2014XNFanSZhang,
  title = {lncRNA-MFDL: Identification of human long non-coding RNAs by fusing multiple features and using deep learning},
  author = {XN Fan, S Zhang}
}


@misc{2014XQinSXiao,
  title = {Transparent-supported radiance regression function},
  author = {X Qin, S Xiao}
}


@misc{2014XWangDFFouheyAGupta,
  title = {Designing Deep Networks for Surface Normal Estimation},
  author = {X Wang, DF Fouhey, A Gupta}
}


@misc{2014XWangJChenWFangCLiangCZhangRHu,
  title = {Pedestrian Detection From Salient Regions},
  author = {X Wang, J Chen, W Fang, C Liang, C Zhang, R Hu}
}


@misc{2014XWangaWTanbHWuc,
  title = {An Innovative Svm for Wheat Seed Quality Estimation⋆},
  author = {X Wanga, W Tanb, H Wuc}
}


@misc{2014YBengioIJGoodfellowACourville,
  title = {Deep Learning},
  author = {Y Bengio, IJ Goodfellow, A Courville}
}


@misc{2014YBurdaRBGrosseRSalakhutdinov,
  title = {Accurate and Conservative Estimates of Mrf Log-likelihood using Reverse Annealing},
  author = {Y Burda, RB Grosse, R Salakhutdinov}
}


@misc{2014YCaoYChenDKhosla,
  title = {Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition},
  author = {Y Cao, Y Chen, D Khosla}
}


@misc{2014YChenMZhuNEpainCJin,
  title = {Unsupervised feature learning on monaural Doa estimation using convolutional deep belief networks},
  author = {Y Chen, M Zhu, N Epain, C Jin}
}


@misc{2014YJinHPTan,
  title = {Unisense: A Unified and Sustainable Sensing and Transport Architecture for Large Scale and Heterogeneous Sensor Networks},
  author = {Y Jin, HP Tan}
}


@misc{2014YLiLMPoXXuLFengFYuanCHCheung,
  title = {No-reference image quality assessment with shearlet transform and deep neural Networks},
  author = {Y Li, LM Po, X Xu, L Feng, F Yuan, CH Cheung}
}


@misc{2014YLiuLQinZChengYZhangWZhangQHuang,
  title = {Da-ccd: A novel action representation by deep architecture of local depth feature},
  author = {Y Liu, L Qin, Z Cheng, Y Zhang, W Zhang, Q Huang}
}


@misc{2014YLiuPLasangMSiegelQSun,
  title = {Geodesic Invariant Feature (gif): A Local Descriptor in Depth},
  author = {Y Liu, P Lasang, M Siegel, Q Sun}
}


@misc{2014YMaZGuoJSuYChenXDuYYangCLiYLin,
  title = {Deep learning for fault diagnosis based on multi-sourced heterogeneous data},
  author = {Y Ma, Z Guo, J Su, Y Chen, X Du, Y Yang, C Li, Y Lin}
}


@misc{2014YPuXYuanLCarin,
  title = {Bayesian Deep Deconvolutional Learning},
  author = {Y Pu, X Yuan, L Carin}
}


@misc{2014YSChouCWSu,
  title = {Personalized Face Image Retrieval Based On Gmkl},
  author = {YS Chou, CW Su}
}


@misc{2014YSJeongRJayaramam,
  title = {Support Vector-Based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification},
  author = {YS Jeong, R Jayaramam}
}


@misc{2014YShiaAKaratzogloubLBaltrunasbMLarsonc,
  title = {Cars2: Learning Context-aware Representations for Context-aware Recommendations},
  author = {Y Shia, A Karatzogloub, L Baltrunasb, M Larsonc}
}


@misc{2014YSunXWangXTang,
  title = {Deeply learned face representations are sparse, selective, and robust},
  author = {Y Sun, X Wang, X Tang}
}


@misc{2014YTTsaiMCYeh,
  title = {Feature Selection And Extraction For Babyface Recognition},
  author = {YT Tsai, MC Yeh}
}


@misc{2014YTaoHChenCQiu,
  title = {Wind Power Prediction and Pattern Feature Based on Deep Learning Method},
  author = {Y Tao, H Chen, C Qiu}
}


@misc{2014YTianPLuoXWangXTang,
  title = {Pedestrian Detection aided by Deep Learning Semantic Tasks},
  author = {Y Tian, P Luo, X Wang, X Tang}
}


@misc{2014YWangGWCottrell,
  title = {Bikers are like tobacco shops, formal dressers are like suits: Recognizing Urban Tribes with Caffe},
  author = {Y Wang, GW Cottrell}
}


@misc{2014YWangSHu,
  title = {Exploiting high level feature for dynamic textures recognition},
  author = {Y Wang, S Hu}
}


@misc{2014YYangJEisenstein,
  title = {Unsupervised Domain Adaptation with Feature Embeddings},
  author = {Y Yang, J Eisenstein}
}


@misc{2014YYangYLiYAloimonos,
  title = {Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web},
  author = {Y Yang, Y Li, Y Aloimonos}
}


@misc{2014YYinMJLiaoXLLi,
  title = {Pedestrian Detection Based on Multi-Stage Unsupervised Learning},
  author = {Y Yin, MJ Liao, XL Li}
}


@misc{2014YZhangCShang,
  title = {Combining Newton interpolation and deep learning for image classification},
  author = {Y Zhang, C Shang}
}


@misc{2014YZhangZTangCZhangJLiuHLu,
  title = {Automatic face annotation in Tv series by video/script alignment},
  author = {Y Zhang, Z Tang, C Zhang, J Liu, H Lu}
}


@misc{2014ZBO,
  title = {A Biologically Inspired Human Posture Recognition System},
  author = {Z BO}
}


@misc{2014ZCaoSLiYLiuWLiHJi,
  title = {A Novel Neural Topic Model and Its Supervised Extension},
  author = {Z Cao, S Li, Y Liu, W Li, H Ji}
}


@misc{2014ZLiuPLuoXWangXTang,
  title = {Deep Learning Face Attributes in the Wild},
  author = {Z Liu, P Luo, X Wang, X Tang}
}


@misc{2014ZLiuQHuangJLiQWang,
  title = {Single image super-resolution via L0 image smoothing},
  author = {Z Liu, Q Huang, J Li, Q Wang}
}


@misc{2014ZLiuQHuangJLiQWangSingleImageSuper-Resolution,
  title = {Single Image Super-Resolution via Image Smoothing},
  author = {Z Liu, Q Huang, J Li, Q Wang}
}


@misc{2014ZLuAMayKLiuABGarakaniDGuoABelletLFan,
  title = {How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets},
  author = {Z Lu, A May, K Liu, AB Garakani, D Guo, A Bellet, L Fan}
}


@misc{2014ZMaoCMaTHMHuangYChenYHuang,
  title = {Bimmer: a novel algorithm for detecting differential Dna methylation regions from MBDCap-seq data},
  author = {Z Mao, C Ma, THM Huang, Y Chen, Y Huang}
}


@misc{2014ZWangJYangHJinEShechtmanAAgarwala,
  title = {Decomposition-Based Domain Adaptation for Real-World Font Recognition},
  author = {Z Wang, J Yang, H Jin, E Shechtman, A Agarwala}
}


@misc{2014ZWuYZhangFYuJXiao,
  title = {A Gpu Implementation of GoogLeNet},
  author = {Z Wu, Y Zhang, F Yu, J Xiao}
}


@misc{2014ZWuZYuJYuanJZhang,
  title = {A twice face recognition algorithm},
  author = {Z Wu, Z Yu, J Yuan, J Zhang}
}


@misc{2014ZYanHZhangBWangSParisYYu,
  title = {Automatic Photo Adjustment Using Deep Learning},
  author = {Z Yan, H Zhang, B Wang, S Paris, Y Yu}
}


@misc{2014ZZhuPLuoXWangXTang,
  title = {Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations},
  author = {Z Zhu, P Luo, X Wang, X Tang}
}


@misc{2015HManoBSeymour,
  title = {Pain: a distributed brain information network?},
  author = {H Mano, B Seymour}
}


@misc{2015JZhangSNguyenYShangDXuIKosztin,
  title = {Fast loop modeling for protein structures},
  author = {J Zhang, S Nguyen, Y Shang, D Xu, I Kosztin}
}


@misc{2015RAManapLShao,
  title = {Non-Distortion-Specific no-reference image quality assessment: A survey},
  author = {RA Manap, L Shao}
}


@misc{2015YHouCWangYJi,
  title = {The Research of Event Detection and Characterization Technology of Ticket Gate in the Urban Rapid Rail Transit},
  author = {Y Hou, C Wang, Y Ji}
}


@misc{2015YLiuXFengZZhou,
  title = {Multimodal Video Classification with Stacked Contractive Autoencoders},
  author = {Y Liu, X Feng, Z Zhou}
}

,

About Amund Tveit (@atveit - amund@memkite.com)

Amund Tveit works in Memkite on developing large-scale Deep Learning and Search (Convolutional Neural Network) with Swift and Metal for iOS (see deeplearning.education for a Memkite app video demo). He also maintains the deeplearning.university bibliography (github.com/memkite/DeepLearningBibliography)

Amund previously co-founded Atbrox , a cloud computing/big data service company (partner with Amazon Web Services), also doing some “sweat equity” startup investments in US and Nordic startups. His presentations about Hadoop/Mapreduce Algorithms and Search were among top 3% of all SlideShare presentations in 2013 and his blog posts has been frequently quoted by Big Data Industry Leaders and featured on front pages of YCombinator News and Reddit Programming

He previously worked for Google, where he was tech.lead for Google News for iPhone (mentioned as “Google News Now Looks Beautiful On Your iPhone” on Mashable.com), lead a team measuring and improving Google Services in the Scandinavian Countries (Maps and Search) and worked as a software engineer on infrastructure projects. Other work experience include telecom (IBM Canada) and insurance/finance (Storebrand).

Amund has a PhD in Computer Science. His publications has been cited more than 500 times. He also holds 4 US patents in the areas of search and advertisement technology, and a pending US patent in the area of brain-controlled search with consumer-level EEG devices.

Amund enjoys coding, in particular Python, C++ and Swift (iOS)

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