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Update with 162 new papers to Deeplearning.University Bibliography

Added 162 new Deep Learning papers to the Deeplearning.University Bibliography, if you want to see them separate from the previous papers in the bibliography the new ones are listed below. There are many highly interesting papers, a few examples are:

  1. Deep neural network based load forecast – forecasts of electricity prediction
  2. The relation of eye gaze and face pose: Potential impact on speech recognition – combining speech recognition with facial expression
  3. Feature Learning from Incomplete EEG with Denoising Autoencoder – Deep Learning for Brain Computer Interfaces

Underneath are the 162 new papers, enjoy!

(Complete Bibliography – at Deeplearning.University Bibliography)

Disclaimer: we’re so far only covering (subset of) 2014 deep learning papers, so still far from a complete bibliography, but our goal is to come close eventuallly

Best regards,

Amund Tveit (Memkite Team)

Links to Deep Learning Subtopics

[3d] [algorithm] [applications] [architecture] [asynchronous][autoencoder] [autogression] [autoregression] [big data] [bioinformatics] [biology] [brain] [convex optimization] [convoluational neural network] [convolutional network] [convolutional neural network] [convolutional neural networks] [deep belief network] [deep convex networks] [deep neural network] [deeply-supervised nets] [digit recognition] [education] [eeg] [electricity forecast] [encoding] [ensemble learning] [face detection] [face recognition] [feature extraction] [finance] [fingerprint recognition] [games] [generative] [gesture recognition] [gpu] [hadoop] [handwriting recognition] [image de-noising] [image recognition] [mahout] [medicine] [mobile] [motion detection] [motion recognition] [music] [natural language processing] [network] [noise] [noiseness] [non-euclidian] [numerics] [online learning] [parallelization] [pose recognition] [posture recognition] [pretraining] [programming language processing] [quantum computing] [recommender systems] [restricted boltzmann machine] [restricted boltzmann machines] [robotics] [scalability] [sequence learning] [smart homes] [sound] [sparseness] [speech recognition] [support vector machines] [survey] [time series] [topic modelling] [traffic] [transfer learning][web spam]

3D

  1. 3d object retrieval with stacked local convolutional autoencoder
  2. Deep Learning Representation using Autoencoder for 3d Shape Retrieval
  3. Local deep feature learning framework for 3d shape
  4. Human gesture recognition using three-dimensional integral imaging

 

Algorithm

  1. Karush-Kuhn-Tucker meets David Hubel and Torsten Weisel through Gabriel Kreiman and Andrew Ng: A connection between highlights of constrained convex..
  2. Learning Deep Representations via Extreme Learning Machines
  3. Recognizing human activity in smart home using deep learning algorithm
  4. Going Deeper with Convolutions
  5. Parallel batch pattern training algorithm for deep neural network
  6. Improved Perception-Based Spiking Neuron Learning Rule for Real-Time User Authentication
  7. Unsupervised Domain Adaptation by Backpropagation
  8. Zero-Shot Learning with Structured Embeddings
  9. Autoencoder Trees
  10. Classifying Gray-scale Sar Images: Adeep Learning Approach
  11. Maximum Reconstruction Probability Training Of Restricted Boltzmann Machines With Auxiliary Function Approach
  12. Deep Sequential Neural Network
  13. Finding quasi core with simulated stacked neural networks
  14. Understanding Locally Competitive Networks
  15. Accuracy evaluation of deep belief networks with fixed-point arithmetic
  16. On the Computational Efficiency of Training Neural Networks
  17. SimNets: A Generalization of Convolutional Networks
  18. Semantics of Visual Discrimination
  19. Temporal Coherence in Energy-based Deep Learning Machines for Action Recognition
  20. The Potential Energy of an Autoencoder

 

Applications

  1. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects
  2. Traffic Flow Prediction With Big Data: A Deep Learning Approach

 

Architecture

  1. Project Adam: Building an Efficient and Scalable Deep Learning Training System

 

Asynchronous

  1. Distributed Asynchronous Optimization of Convolutional Neural Networks
  2. Contour Motion Estimation for Asynchronous Event-Driven Cameras

 

Audio

  1. Chord Recognition with Stacked Denoising Autoencoders
  2. A Deep Neural Network Approach to Automatic Birdsong Recognition

 

Autoencoder

  1. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  2. 3d object retrieval with stacked local convolutional autoencoder
  3. Chord Recognition with Stacked Denoising Autoencoders
  4. Deep Learning Representation using Autoencoder for 3d Shape Retrieval
  5. Autoencoder Trees
  6. Deep Directed Generative Autoencoders
  7. Feature Learning from Incomplete Eeg with Denoising Autoencoder
  8. The Potential Energy of an Autoencoder

 

Autogression

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

 

Autoregression

  1. A Neural Autoregressive Approach to Attention-based Recognition

 

Big Data

  1. Project Adam: Building an Efficient and Scalable Deep Learning Training System
  2. Traffic Flow Prediction With Big Data: A Deep Learning Approach

 

Bioinformatics

  1. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network
  2. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects

 

Biology

  1. Image-Based Analysis to Study Plant Infection with Human Pathogens

 

Brain

  1. Feature Learning from Incomplete Eeg with Denoising Autoencoder

 

Convex Optimization

  1. Convolutional Neural Network and Convex Optimization

 

Convoluational Neural Network

  1. Context Dependent Encoding using Convolutional Dynamic Networks

 

Convolutional Network

  1. Real-time continuous pose recovery of human hands using convolutional networks
  2. Vehicle License Plate Recognition With Random Convolutional Networks
  3. SimNets: A Generalization of Convolutional Networks

 

Convolutional Neural Network

  1. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  2. Handwritten Hangul recognition using deep convolutional neural networks
  3. Modelling ‚Visualising and Summarising Documents with a Single Convolutional Neural Network
  4. Distributed Asynchronous Optimization of Convolutional Neural Networks
  5. An Efficient Implementation of Deep Convolutional Neural Networks on a Mobile Coprocessor
  6. Weighted Convolutional Neural Network Ensemble
  7. Deep convolutional neural networks for large-scale speech tasks
  8. Deformable Part Models are Convolutional Neural Networks
  9. Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks
  10. Going Deeper with Convolutions
  11. Tbcnn: A Tree-Based Convolutional Neural Network for Programming Language Processing
  12. 3d object retrieval with stacked local convolutional autoencoder
  13. A convolutional neural network approach for face verification
  14. Spatially-sparse convolutional neural networks
  15. Deep Convolutional Neural Networks With An Application Towards Geospatial Object Recognition
  16. Convolutional Neural Network and Convex Optimization

 

Convolutional Neural Networks

  1. Memory Access Optimized Scheduling Scheme for DCNNs on a Mobile Processor

 

Deep Belief Network

  1. Camera-based Sudoku recognition with Deep Belief Network
  2. Prediction of Stock Trend Based on Deep Belief Networks
  3. Deep Tempering
  4. Accuracy evaluation of deep belief networks with fixed-point arithmetic

 

Deep Convex Networks

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

 

Deep Neural Network

  1. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network
  2. Recognition Of Acoustic Events Using Deep Neural Networks
  3. Audio Concept Classification With Hierarchical Deep Neural Networks
  4. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training
  5. Classification of Artistic Styles using Binarized Features Derived from a Deep Neural Network
  6. Deep neural network based load forecast
  7. Parallel batch pattern training algorithm for deep neural network
  8. Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network
  9. Qr Code Localization Using Deep Neural Networks
  10. Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition
  11. A Real-time Hand Posture Recognition System Using Deep Neural Networks
  12. A Deep Neural Network Approach to Automatic Birdsong Recognition
  13. Binaural Classification for Reverberant Speech Segregation Using Deep Neural Networks

 

Deeply-Supervised Nets

  1. Deeply-Supervised Nets

 

Digit Recognition

  1. Robust continuous digit recognition using reservoir computing

 

Education

  1. Contexto: lessons learned from mobile context inference

 

Eeg

  1. Feature Learning from Incomplete Eeg with Denoising Autoencoder

 

Electricity Forecast

  1. Deep neural network based load forecast

 

Encoding

  1. Two-layer contractive encodings for learning stable nonlinear features

 

Ensemble Learning

  1. Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning

 

Face Detection

  1. Detecting People in Cubist Art

 

Face Recognition

  1. Recognition of Facial Attributes using Adaptive Sparse Representations of Random Patches
  2. Hough Networks for Head Pose Estimation and Facial Feature Localization
  3. A Neural Autoregressive Approach to Attention-based Recognition
  4. Recognition of Facial Expression via Kernel Pca Network
  5. Deep Regression for Face Alignment
  6. A convolutional neural network approach for face verification
  7. Facial Landmark Localization using Hierarchical Pose Regression
  8. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  9. A Deep Graph Embedding Network Model for Face Recognition
  10. Learning Multiscale Active Facial Patches for Expression Analysis
  11. Fast Localization of Facial Landmark Points
  12. The relation of eye gaze and face pose: Potential impact on speech recognition
  13. Low rank driven robust facial landmark regression
  14. Deep Representations for Iris, Face, and Fingerprint Spoofing Attack Detection
  15. Facial Feature Point Detection: A Comprehensive Survey
  16. Learning Invariant Color Features for Person Re-Identification

 

Feature Extraction

  1. Audio-only bird classification using unsupervised feature learning
  2. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  3. Feature Selection Based on Dependency Margin
  4. Improving Acoustic Model for Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Bottleneck Features
  5. Local deep feature learning framework for 3d shape

 

Finance

  1. Gpu Implementation of a Deep Learning Network for Financial Prediction

 

Fingerprint Recognition

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

 

Games

  1. Camera-based Sudoku recognition with Deep Belief Network

 

Generative

  1. Generative Adversarial Nets

 

Gesture Recognition

  1. Deep Dynamic Neural Networks for Gesture Segmentation and Recognition
  2. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  3. A Study of Feature Combination in Gesture Recognition with Kinect

 

Gpu

  1. Determining the difficulty of accelerating problems on a Gpu
  2. Optimising Purely Functional Gpu Programs (Thesis)
  3. Gpu Implementation of a Deep Learning Network for Financial Prediction
  4. cuDNN: Efficient Primitives for Deep Learning

 

Hadoop

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

 

Handwriting Recognition

  1. Icfhr2014 Competition on Handwritten Text Recognition on tranScriptorium Datasets (HTRtS)
  2. Writer Adaptation using Bottleneck Features and Discriminative Linear Regression for Online Handwritten Chinese Character Recognition
  3. Deep-Belief-Network based Rescoring for Handwritten Word Recognition
  4. Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition
  5. A Tibetan Component Representation Learning Method for Online Handwritten Tibetan Character Recognition

 

Image De-Noising

  1. Image De-Noising Using Deep Learning

 

Image Recognition

  1. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
  2. Handwritten Hangul recognition using deep convolutional neural networks
  3. Joint Road Network Extraction From A Set Of High Resolution Satellite Images
  4. Self-taught Object Localization with Deep Networks
  5. Ibm research australia at lifeclef2014: Plant identification task
  6. MindLab at ImageCLEF 2014: Scalable Concept Image Annotation
  7. Sabanci-okan system at lifeclef 2014 plant identification competition
  8. Image classification via learning dissimilarity measure in non-euclidean spaces
  9. Compute Less to Get More: Using Orc to Improve Sparse Filtering
  10. Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks
  11. Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning
  12. Mlia at ImageCLFE 2014 Scalable Concept Image Annotation Challenge
  13. Random Cascaded-Regression Copse for Robust Facial Landmark Detection
  14. Contour Motion Estimation for Asynchronous Event-Driven Cameras
  15. Difference representation learning using stacked restricted Boltzmann machines for change detection in Sar images
  16. Object Classification via PCANet and Color Constancy Model
  17. The Application of Sift Image Matching in the Information Query Based on Mpi Acceleration
  18. Defect Detecting Technology Based on Machine Vision of Industrial Parts
  19. Neural Networks and Neuroscience-Inspired Computer Vision
  20. Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification
  21. 1-hkust: Object Detection in Ilsvrc 2014
  22. Domain Adaptive Neural Networks for Object Recognition
  23. Image Classification with A Deep Network Model based on Compressive Sensing
  24. Do More Dropouts in Pool5 Feature Maps for Better Object Detection
  25. Continuous gesture recognition from articulated poses
  26. Image-Based Analysis to Study Plant Infection with Human Pathogens
  27. Free-Form Region Description with Second-Order Pooling
  28. MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
  29. Hyper-Spectral Image Analysis with Partially-Latent Regression and Spatial Markov Dependencies
  30. Classifying Gray-scale Sar Images: Adeep Learning Approach
  31. Qr Code Localization Using Deep Neural Networks
  32. Localization of Visual Codes in the Dct Domain Using Deep Rectifier Neural Networks
  33. Deep Convolutional Neural Networks With An Application Towards Geospatial Object Recognition
  34. Vehicle License Plate Recognition With Random Convolutional Networks
  35. Human gesture recognition using three-dimensional integral imaging
  36. Saliency-guided deep framework for image quality assessment
  37. Helping robots see the big picture
  38. Exploiting the deep learning paradigm for recognizing human actions
  39. Deep Model for Classification of Hyperspectral image using Restricted Boltzmann Machine
  40. HAck: A system for the recognition of human actions by kernels of visual strings
  41. Explain Images with Multimodal Recurrent Neural Networks
  42. Deep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning
  43. Semantics of Visual Discrimination
  44. Multi-View Semi-Supervised Learning Based Image Annotation

 

Mahout

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

 

Medicine

  1. Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects

 

Mobile

  1. An Efficient Implementation of Deep Convolutional Neural Networks on a Mobile Coprocessor
  2. Memory Access Optimized Scheduling Scheme for DCNNs on a Mobile Processor
  3. Contexto: lessons learned from mobile context inference

 

Motion Detection

  1. Contour Motion Estimation for Asynchronous Event-Driven Cameras

 

Motion Recognition

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

 

Music

  1. Chord Recognition with Stacked Denoising Autoencoders

 

Natural Language Processing

  1. Modelling ‚Visualising and Summarising Documents with a Single Convolutional Neural Network
  2. Introduction to Word2vec and its application to find predominant word senses
  3. Rc-net: A General Framework for Incorporating Knowledge into Word Representations
  4. Analyzing sparse dictionaries for online learning with kernels

 

Network

  1. Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network

 

Noise

  1. Chord Recognition with Stacked Denoising Autoencoders

 

Noiseness

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

 

Non-Euclidian

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

 

Numerics

  1. Accuracy evaluation of deep belief networks with fixed-point arithmetic

 

Online Learning

  1. Analyzing sparse dictionaries for online learning with kernels

 

Parallelization

  1. Parallel batch pattern training algorithm for deep neural network
  2. The Application of Sift Image Matching in the Information Query Based on Mpi Acceleration

 

Pose Recognition

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

 

Posture Recognition

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

 

Pretraining

  1. Assessment of Electrocardiograms with Pretraining and Shallow Networks

 

Programming Language Processing

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

 

Quantum Computing

  1. An introduction to quantum machine learning

 

Recommender Systems

  1. Collaborative Deep Learning for Recommender Systems

 

Restricted Boltzmann Machine

  1. To be Bernoulli or to be Gaussian, for a Restricted Boltzmann Machine
  2. Deep neural network based load forecast
  3. Expected energy-based restricted Boltzmann machine for classification
  4. A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development
  5. Deep Tempering
  6. A Novel Inference of a Restricted Boltzmann Machine
  7. Deep Model for Classification of Hyperspectral image using Restricted Boltzmann Machine

 

Restricted Boltzmann Machines

  1. Difference representation learning using stacked restricted Boltzmann machines for change detection in Sar images
  2. Maximum Reconstruction Probability Training Of Restricted Boltzmann Machines With Auxiliary Function Approach

 

Robotics

  1. Helping robots see the big picture

 

Scalability

  1. Scaling Distributed Machine Learning with the Parameter Server

 

Sequence Learning

  1. Sequence to Sequence Learning with Neural Networks

 

Smart Homes

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

 

Sound

  1. Recognition Of Acoustic Events Using Deep Neural Networks
  2. Audio Concept Classification With Hierarchical Deep Neural Networks
  3. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training

 

Sparseness

  1. A linear approach for sparse coding by a two-layer neural network
  2. Static hand gesture recognition using stacked Denoising Sparse Autoencoders
  3. Compute Less to Get More: Using Orc to Improve Sparse Filtering
  4. Spatially-sparse convolutional neural networks
  5. Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
  6. Analyzing sparse dictionaries for online learning with kernels

 

Speech Recognition

  1. Voice Conversion Using Deep Neural Networks with Layer-Wise Generative Training
  2. Deep convolutional neural networks for large-scale speech tasks
  3. A Deep Learning Approach to Data-driven Parameterizations for Statistical Parametric Speech Synthesis
  4. Improving Acoustic Model for Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Bottleneck Features
  5. The relation of eye gaze and face pose: Potential impact on speech recognition
  6. Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments
  7. Binaural Classification for Reverberant Speech Segregation Using Deep Neural Networks
  8. Computational modeling and validation of the motor contribution to speech perception

 

Support Vector Machines

  1. Deep learning of support vector machines with class probability output networks

 

Survey

  1. Deep Learning for Content-Based Image Retrieval: A Comprehensive Study
  2. Facial Feature Point Detection: A Comprehensive Survey

 

Time Series

  1. Learning Methods for Variable Selection and Time Series Prediction

 

Topic Modelling

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

 

Traffic

  1. Traffic Flow Prediction With Big Data: A Deep Learning Approach

 

Transfer Learning

  1. Transfer Learning for Video Recognition with Scarce Training Data

 

Video

  1. Machine Learning in Intelligent Video and Automated Monitoring
  2. Transfer Learning for Video Recognition with Scarce Training Data
  3. Effects on learning of multimedia animation combined with multidimensional concept maps
  4. MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
  5. A Study of Feature Combination in Gesture Recognition with Kinect

 

Web Spam

  1. Comparisons of machine learning techniques for detecting malicious webpages

 

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@misc{2014ADeleforgeFForbesSBaRHoraud,
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@misc{2014ADundarJJinVGokhaleBMartiniECulurciello,
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@misc{2014AJainJTompsonYLeCunCBregler,
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@misc{2014AJalalvandFTriefenbachKDemuynckJPMartens,
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@misc{2014AMontaltoGTessitoreRPrevete,
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@misc{2014AOIbraheem,
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@misc{2014AOTANGKELUYWANGJIEHUANGHLI,
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@misc{2014ASchwarzCHuemmerRMaasWKellermann,
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@misc{2014BLengSGuoXZhangZXiong,
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@misc{2014BShiXBaiWLiuJWang,
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@misc{2014BWichtJHennebert,
  title = {Camera-based Sudoku recognition with Deep Belief Network},
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@misc{2014BYanikogluYSTolgaCTirkazEFuenCaglartes,
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}


@misc{2014CCChiouLCTienLTLee,
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@misc{2014CJSunSHZhuZShi,
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@misc{2014CLIXXIEYHUANGHWangCNIU,
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@misc{2014CLuHChenQChenHLawYXiaoCKTang,
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@misc{2014CSzegedyWLiuYJiaPSermanetSReed,
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@misc{2014CXuYBaiJBianBGaoGWangXLiuTYLiu,
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@misc{2014CYLeeSXiePGallagherZZhangZTu,
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@misc{2014DDCoxTDean,
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@misc{2014DKHuASYeLLiLZhang,
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}


@misc{2014DKHuLZhangWDZhaoTYan,
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@misc{2014DMenottiGChiachiaAPintoWRSchwartzHPedrini,
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@misc{2014DMenottiGChiachiaAXFalcaoVJONeto,
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@misc{2014DMeryKBowyer,
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@misc{2014DSovilj,
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@misc{2014DStowellMDPlumbley,
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}


@misc{2014DTristramKBradshaw,
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@misc{2014DWuLShao,
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}


@misc{2014EBATI,
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}


@misc{2014FBarrancoCFermullerYAloimonos,
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}


@misc{2014GChenSNSrihari,
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}


@misc{2014GDesjardinsHLuoACourvilleYBengio,
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}


@misc{2014GEvangelidisGSinghRHoraud,
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@misc{2014GRieglerDFerstlMRütherHBischof,
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@misc{2014HBKazemianSAhmed,
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@misc{2014HFangCHu,
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@misc{2014HKamyshanskaRMemisevic,
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@misc{2014HQuXXieYLiuMZhangLLu,
  title = {Improved Perception-Based Spiking Neuron Learning Rule for Real-Time User Authentication},
  author = {H Qu, X Xie, Y Liu, M Zhang, L Lu}
}


@misc{2014HSchulzKChoTRaikoSBehnke,
  title = {Two-layer contractive encodings for learning stable nonlinear features},
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@misc{2014HVKoops,
  title = {A Deep Neural Network Approach to Automatic Birdsong Recognition},
  author = {HV Koops}
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@misc{2014HWang,
  title = {Introduction to Word2vec and its application to find predominant word senses},
  author = {H Wang}
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@misc{2014HWangClassifyingGray-scaleSar,
  title = {Classifying Gray-scale Sar Images: Adeep Learning Approach},
  author = {H Wang}
}


@misc{2014HWangNWangDYYeung,
  title = {Collaborative Deep Learning for Recommender Systems},
  author = {H Wang, N Wang, DY Yeung}
}


@misc{2014ICortesCirianoQulAinVSubramanianBLenselink,
  title = {Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects},
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}


@misc{2014IJGoodfellowJPougetAbadieMMirzaBXu,
  title = {Generative Adversarial Nets},
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}


@misc{2014IJKimXXie,
  title = {Handwritten Hangul recognition using deep convolutional neural networks},
  author = {IJ Kim, X Xie}
}


@misc{2014ISutskeverOVinyalsQVLe,
  title = {Sequence to Sequence Learning with Neural Networks},
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}


@misc{2014JASánchezVRomeroAHToselliEVidal,
  title = {Icfhr2014 Competition on Handwritten Text Recognition on tranScriptorium Datasets (HTRtS)},
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}


@misc{2014JAVanegasJArevaloSOtáloraFPáez,
  title = {MindLab at ImageCLEF 2014: Scalable Concept Image Annotation},
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}


@misc{2014JBohannon,
  title = {Helping robots see the big picture},
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}


@misc{2014JCarreiraRCaseiroJBatistaCSminchisescu,
  title = {Free-Form Region Description with Second-Order Pooling},
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@misc{2014JDoshiCMasonAWagnerZKira,
  title = {Deep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning},
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}


@misc{2014JDu,
  title = {Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition},
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}


@misc{2014JDuJSHuBZhuSWeiLRDai,
  title = {Writer Adaptation using Bottleneck Features and Discriminative Linear Regression for Online Handwritten Chinese Character Recognition},
  author = {J Du, JS Hu, B Zhu, S Wei, LR Dai}
}


@misc{2014JJiangRHuLMikelYDou,
  title = {Accuracy evaluation of deep belief networks with fixed-point arithmetic},
  author = {J Jiang, R Hu, L Mikel, Y Dou}
}


@misc{2014JJinVGokhaleADundarBKrishnamurthyBMartini,
  title = {An Efficient Implementation of Deep Convolutional Neural Networks on a Mobile Coprocessor},
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@misc{2014JLedererSGuadarrama,
  title = {Compute Less to Get More: Using Orc to Improve Sparse Filtering},
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@misc{2014JLiZStruzikLZhangACichocki,
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@misc{2014JLiuMGongJZhaoHLiLJiao,
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@misc{2014JLyonsADehzangiRHeffernanASharma,
  title = {Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network},
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}


@misc{2014JMaoWXuYYangJWangALYuille,
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}


@misc{2014JRSmith,
  title = {Semantics of Visual Discrimination},
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@misc{2014JTompsonMSteinYLecunKPerlin,
  title = {Real-time continuous pose recovery of human hands using convolutional networks},
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@misc{2014JWanDWangSCHHoiPWuJZhuYZhangJLi,
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}


@misc{2014JYYu,
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@misc{2014LBadinoADAusilioLFadigaGMetta,
  title = {Computational modeling and validation of the motor contribution to speech perception},
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@misc{2014LBrunGPercannellaASaggeseMVento,
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}


@misc{2014LChenSZhuZLiJHu,
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}


@misc{2014LDengXHeGTurDHakkanitur,
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@misc{2014LDenoyerPGallinari,
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@misc{2014LHChenZHLingLJLiuLRDai,
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@misc{2014LLMaJWu,
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@misc{2014LMouGLiZJinLZhangTWang,
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@misc{2014LZhangYFNieZHWang,
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}


@misc{2014LZhongQLiuPYangJHuangDNMetaxas,
  title = {Learning Multiscale Active Facial Patches for Expression Analysis},
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}


@misc{2014MBhattacharyyaSBandyopadhyay,
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@misc{2014MEMidhunSRNairVTPrabhakarSSKumar,
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@misc{2014MGhifaryWBKleijnMZhang,
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@misc{2014MKhalilHaniLSSung,
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@misc{2014MLiDGAndersenJWParkAJSmolaAAhmed,
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@misc{2014MRavanelliBElizaldeKNiGFriedlandFBKessler,
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}


@misc{2014MSchikoraASchikora,
  title = {Image-Based Analysis to Study Plant Infection with Human Pathogens},
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@misc{2014MSchuldISinayskiyFPetruccione,
  title = {An introduction to quantum machine learning},
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@misc{2014MSlaneyAStolckeDHakkaniTur,
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}


@misc{2014MTanakaMOkutomi,
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@misc{2014MUngerLRokachABarEGudesBShapira,
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@misc{2014NCohenAShashua,
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@misc{2014NMarkušMFrljakISPandzicJAhlberg,
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}


@misc{2014NQPhamHSLeDDNguyenTGNgo,
  title = {A Study of Feature Combination in Gesture Recognition with Kinect},
  author = {NQ Pham, HS Le, DD Nguyen, TG Ngo}
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@misc{2014NSteenbergen,
  title = {Chord Recognition with Stacked Denoising Autoencoders},
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}


@misc{2014NTakamuneHKameoka,
  title = {Maximum Reconstruction Probability Training Of Restricted Boltzmann Machines With Auxiliary Function Approach},
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}


@misc{2014NWangXGaoDTaoXLi,
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}


@misc{2014NdeFreitas,
  title = {Modelling ‚Visualising and Summarising Documents with a Single Convolutional Neural Network},
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@misc{2014OBesbesABenazzaBenyahia,
  title = {Joint Road Network Extraction From A Set Of High Resolution Satellite Images},
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@misc{2014OGencogluTVirtanenHHuttunen,
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@misc{2014OİrsoyEAlpaydın,
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@misc{2014PBodnárTGrószLTóthLGNyúl,
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@misc{2014PFengMYuSMNaqviJAChambers,
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@misc{2014PFoggiaASaggeseNStrisciuglioMVento,
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@misc{2014PHOPinheiroRCollobert,
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@misc{2014PHoneine,
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@misc{2014PKMuthukumarAWBlack,
  title = {A Deep Learning Approach to Data-driven Parameterizations for Statistical Parametric Speech Synthesis},
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@misc{2014PPRoyYChherawalaMCheriet,
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@misc{2014QBNguyenTTVuCMLuong,
  title = {Improving Acoustic Model for Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Bottleneck Features},
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@misc{2014QChenMAbediniRGarnaviXLiang,
  title = {Ibm research australia at lifeclef2014: Plant identification task},
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}


@misc{2014RChalasaniJCPrincipe,
  title = {Context Dependent Encoding using Convolutional Dynamic Networks},
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}


@misc{2014RGirshickFIandolaTDarrellJMalik,
  title = {Deformable Part Models are Convolutional Neural Networks},
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}


@misc{2014RKSrivastavaJMasciFGomezJSchmidhuber,
  title = {Understanding Locally Competitive Networks},
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}


@misc{2014RKumarAKCheema,
  title = {Gpu Implementation of a Deep Learning Network for Financial Prediction},
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}


@misc{2014RLivniSShalevShwartzOShamir,
  title = {On the Computational Efficiency of Training Neural Networks},
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}


@misc{2014RRVariorGWangJLu,
  title = {Learning Invariant Color Features for Person Re-Identification},
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}


@misc{2014RSAdepu,
  title = {Temporal Coherence in Energy-based Deep Learning Machines for Action Recognition},
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}


@misc{2014RWangCHanYWuTGuo,
  title = {Fingerprint Classification Based on Depth Neural Network},
  author = {R Wang, C Han, Y Wu, T Guo}
}


@misc{2014SBuPHanZLiuJHan,
  title = {Local deep feature learning framework for 3d shape},
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}


@misc{2014SChenYWang,
  title = {Convolutional Neural Network and Convex Optimization},
  author = {S Chen, Y Wang}
}


@misc{2014SChetlurCWoolleyPVandermerschJCohen,
  title = {cuDNN: Efficient Primitives for Deep Learning},
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@misc{2014SElfwingEUchibeKDoya,
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@misc{2014SGinosarDHaasTBrownJMalik,
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@misc{2014SKimZYuRMKilMLee,
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@misc{2014SOzairYBengio,
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@misc{2014SPaisitkriangkraiCShenAHengel,
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}


@misc{2014TChilimbiYSuzueJApacibleKKalyanaraman,
  title = {Project Adam: Building an Efficient and Scalable Deep Learning Training System},
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}


@misc{2014TGrószPBodnárLTóthLGNyúl,
  title = {Qr Code Localization Using Deep Neural Networks},
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@misc{2014TLMcDonell,
  title = {Optimising Purely Functional Gpu Programs (Thesis)},
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@misc{2014TNSainathBKingsburyGSaonHSoltau,
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@misc{2014TSLiCMHu,
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@misc{2014TYamashitaMTanakaEYoshidaYYamauchi,
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@misc{2014VJRRipollAWojdelPRamosERomeroJBrugada,
  title = {Assessment of Electrocardiograms with Pretraining and Shallow Networks},
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@misc{2014VJavierTraverPLatorreCarmona,
  title = {Human gesture recognition using three-dimensional integral imaging},
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@misc{2014VKumarGCNandiRKala,
  title = {Static hand gesture recognition using stacked Denoising Sparse Autoencoders},
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@misc{2014VTurchenkoVGolovko,
  title = {Parallel batch pattern training algorithm for deep neural network},
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@misc{2014WChanILaneSGradientsMMomentumGDecay,
  title = {Distributed Asynchronous Optimization of Convolutional Neural Networks},
  author = {W Chan, I Lane, S Gradients, M Momentum, G Decay}
}


@misc{2014WHe,
  title = {Deep neural network based load forecast},
  author = {W He}
}


@misc{2014WHouXGao,
  title = {Saliency-guided deep framework for image quality assessment},
  author = {W Hou, X Gao}
}


@misc{2014WOuyangPLuoXZengSQiuYTianHLiSYang,
  title = {DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection},
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@misc{2014WYuFZhuangQHeZShi,
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}


@misc{2014XFrazaoLAAlexandre,
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@misc{2014XJHeZDYiJLiuYZWang,
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@misc{2014XJWu,
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@misc{2014XPengRYanBZhaoHTangZYi,
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}


@misc{2014XXuAShimadaRTaniguchi,
  title = {Mlia at ImageCLFE 2014 Scalable Concept Image Annotation Challenge},
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}


@misc{2014YBYuanGYDavidSZhao,
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@misc{2014YBarNLevyLWolf,
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@misc{2014YCSuTHChiuCYYehHHuangWHHsu,
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@misc{2014YGanTYangCHe,
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@misc{2014YGanTZhuoCHe,
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@misc{2014YGaninVLempitsky,
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@misc{2014YJiangDWangRLiuZFeng,
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}


@misc{2014YLiuFTangZZeng,
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}


@misc{2014YLvYDuanWKangZLiFYWang,
  title = {Traffic Flow Prediction With Big Data: A Deep Learning Approach},
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}


@misc{2014YSunQLiuHLu,
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@misc{2014YZhengRSZemelYJZhangHLarochelle,
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}


@misc{2014YZhengYJZhangHLarochelle,
  title = {A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data},
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}


@misc{2014ZAkataHLeeBSchiele,
  title = {Zero-Shot Learning with Structured Embeddings},
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}


@misc{2014ZShenXXue,
  title = {Do More Dropouts in Pool5 Feature Maps for Better Object Detection},
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}


@misc{2014ZYXuLNTangCPTian,
  title = {Prediction of Stock Trend Based on Deep Belief Networks},
  author = {ZY Xu, LN Tang, CP Tian}
}


@misc{2014ZZhangWZhangJLiuXTang,
  title = {Facial Landmark Localization using Hierarchical Pose Regression},
  author = {Z Zhang, W Zhang, J Liu, X Tang}
}


@misc{2014ZZhuXWangSBaiCYaoXBai,
  title = {Deep Learning Representation using Autoencoder for 3d Shape Retrieval},
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}

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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