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:

- Deep neural network based load forecast – forecasts of electricity prediction
- The relation of eye gaze and face pose: Potential impact on speech recognition – combining speech recognition with facial expression
- 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,

## 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

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

## Algorithm

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

## Applications

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

## Architecture

## Asynchronous

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

## Audio

- Chord Recognition with Stacked Denoising Autoencoders
- A Deep Neural Network Approach to Automatic Birdsong Recognition

## Autoencoder

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

## Autogression

## Autoregression

## Big Data

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

## Bioinformatics

- Predicting backbone CÎ± angles and dihedrals from protein sequences by stacked sparse autoâ€encoder deep neural network
- Polypharmacology Modelling Using Proteochemometrics (pcm): Recent Methodological Developments, Applications to Target Families, and Future Prospects

## Biology

## Brain

## Convex Optimization

## Convoluational Neural Network

## Convolutional Network

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

## Convolutional Neural Network

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

## Convolutional Neural Networks

## Deep Belief Network

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

## Deep Convex Networks

## Deep Neural Network

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

## Deeply-Supervised Nets

## Digit Recognition

## Education

## Eeg

## Electricity Forecast

## Encoding

## Ensemble Learning

## Face Detection

## Face Recognition

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

## Feature Extraction

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

## Finance

## Fingerprint Recognition

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

## Games

## Generative

## Gesture Recognition

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

## Gpu

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

## Hadoop

## Handwriting Recognition

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

## Image De-Noising

## Image Recognition

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

## Mahout

## Medicine

## Mobile

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

## Motion Detection

## Motion Recognition

## Music

## Natural Language Processing

- Modelling â€šVisualising and Summarising Documents with a Single Convolutional Neural Network
- Introduction to Word2vec and its application to find predominant word senses
- Rc-net: A General Framework for Incorporating Knowledge into Word Representations
- Analyzing sparse dictionaries for online learning with kernels

## Network

## Noise

## Noiseness

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

## Non-Euclidian

## Numerics

## Online Learning

## Parallelization

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

## Pose Recognition

## Posture Recognition

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

## Pretraining

## Programming Language Processing

## Quantum Computing

## Recommender Systems

## Restricted Boltzmann Machine

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

## Restricted Boltzmann Machines

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

## Robotics

## Scalability

## Sequence Learning

## Smart Homes

## Sound

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

## Sparseness

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

## Speech Recognition

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

## Support Vector Machines

## Survey

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

## Time Series

## Topic Modelling

## Traffic

## Transfer Learning

## Video

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

## Web Spam

# BIBLIOGRAPHY

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approach for sparse coding by a two-layer neural network}, author = {A Montalto, G Tessitore, R Prevete} } @misc{2014AOIbraheem, title = {Karush-Kuhn-Tucker meets David Hubel and Torsten Weisel through Gabriel Kreiman and Andrew Ng: A connection between highlights of constrained convex..}, author = {AO Ibraheem} } @misc{2014AOTANGKELUYWANGJIEHUANGHLI, title = {A Real-time Hand Posture Recognition System Using Deep Neural Networks}, author = {AO TANG, KE LU, Y WANG, JIE HUANG, H LI} } @misc{2014ASchwarzCHuemmerRMaasWKellermann, title = {Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments}, author = {A Schwarz, C Huemmer, R Maas, W Kellermann} } @misc{2014BGraham, title = {Spatially-sparse convolutional neural networks}, author = {B Graham} } @misc{2014BHanBHeTSunMMaALendasse, title = {Hsr: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection}, author = {B Han, B He, T Sun, M Ma, A Lendasse} } @misc{2014BLengSGuoXZhangZXiong, title = {3d object retrieval with stacked local convolutional autoencoder}, author = {B Leng, S Guo, X Zhang, Z Xiong} } @misc{2014BShiXBaiWLiuJWang, title = {Deep Regression for Face Alignment}, author = {B Shi, X Bai, W Liu, J Wang} } @misc{2014BWichtJHennebert, title = {Camera-based Sudoku recognition with Deep Belief Network}, author = {B Wicht, J Hennebert} } @misc{2014BYanikogluYSTolgaCTirkazEFuenCaglartes, title = {Sabanci-okan system at lifeclef 2014 plant identification competition}, author = {B Yanikoglu, YS Tolga, C Tirkaz, E FuenCaglartes} } @misc{2014CCChiouLCTienLTLee, title = {Effects on learning of multimedia animation combined with multidimensional concept maps}, author = {CC Chiou, LC Tien, LT Lee} } @misc{2014CJSunSHZhuZShi, title = {Multi-View Semi-Supervised Learning Based Image Annotation}, author = {CJ Sun, SH Zhu, Z Shi} } @misc{2014CLIXXIEYHUANGHWangCNIU, title = {Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network}, author = {C LI, X XIE, Y HUANG, H Wang, C NIU} } @misc{2014CLuHChenQChenHLawYXiaoCKTang, title = {1-hkust: Object Detection in Ilsvrc 2014}, author = {C Lu, H Chen, Q Chen, H Law, Y Xiao, CK Tang} } @misc{2014CSzegedyWLiuYJiaPSermanetSReed, title = {Going Deeper with Convolutions}, author = {C Szegedy, W Liu, Y Jia, P Sermanet, S Reed} } @misc{2014CXuYBaiJBianBGaoGWangXLiuTYLiu, title = {Rc-net: A General Framework for Incorporating Knowledge into Word Representations}, author = {C Xu, Y Bai, J Bian, B Gao, G Wang, X Liu, TY Liu} } @misc{2014CYLeeSXiePGallagherZZhangZTu, title = {Deeply-Supervised Nets}, author = {CY Lee, S Xie, P Gallagher, Z Zhang, Z Tu} } @misc{2014DDCoxTDean, title = {Neural Networks and Neuroscience-Inspired Computer Vision}, author = {DD Cox, T Dean} } @misc{2014DKHuASYeLLiLZhang, title = {Recognition of Facial Expression via Kernel Pca Network}, author = {DK Hu, AS Ye, L Li, L Zhang} } @misc{2014DKHuLZhangWDZhaoTYan, title = {Object Classification via PCANet and Color Constancy Model}, author = {DK Hu, L Zhang, WD Zhao, T Yan} } @misc{2014DMenottiGChiachiaAPintoWRSchwartzHPedrini, title = {Deep Representations for Iris, Face, and Fingerprint Spoofing Attack Detection}, author = {D Menotti, G Chiachia, A Pinto, WR Schwartz, H Pedrini} } @misc{2014DMenottiGChiachiaAXFalcaoVJONeto, title = {Vehicle License Plate Recognition With Random Convolutional Networks}, author = {D Menotti, G Chiachia, AX Falcao, VJO Neto} } @misc{2014DMeryKBowyer, title = {Recognition of Facial Attributes using Adaptive Sparse Representations of Random Patches}, author = {D Mery, K Bowyer} } @misc{2014DSovilj, title = {Learning Methods for Variable Selection and Time Series Prediction}, author = {D Sovilj} } @misc{2014DStowellMDPlumbley, title = {Audio-only bird classification using unsupervised feature learning}, author = {D Stowell, MD Plumbley} } @misc{2014DTristramKBradshaw, title = {Determining the difficulty of accelerating problems on a Gpu}, author = {D Tristram, K Bradshaw} } @misc{2014DWuLShao, title = {Deep Dynamic Neural Networks for Gesture Segmentation and Recognition}, author = {D Wu, L Shao} } @misc{2014EBATI, title = {Deep Convolutional Neural Networks With An Application Towards Geospatial Object Recognition}, author = {E BATI} } @misc{2014FBarrancoCFermullerYAloimonos, title = {Contour Motion Estimation for Asynchronous Event-Driven Cameras}, author = {F Barranco, C Fermuller, Y Aloimonos} } @misc{2014GChenSNSrihari, title = {A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development}, author = {G Chen, SN Srihari} } @misc{2014GDesjardinsHLuoACourvilleYBengio, title = {Deep Tempering}, author = {G Desjardins, H Luo, A Courville, Y Bengio} } @misc{2014GEvangelidisGSinghRHoraud, title = {Continuous gesture recognition from articulated poses}, author = {G Evangelidis, G Singh, R Horaud} } @misc{2014GRieglerDFerstlMRÃ¼therHBischof, title = {Hough Networks for Head Pose Estimation and Facial Feature Localization}, author = {G Riegler, D Ferstl, M RÃ¼ther, H Bischof} } @misc{2014HBKazemianSAhmed, title = {Comparisons of machine learning techniques for detecting malicious webpages}, author = {HB Kazemian, S Ahmed} } @misc{2014HFangCHu, title = {Recognizing human activity in smart home using deep learning algorithm}, author = {H Fang, C Hu} } @misc{2014HKamyshanskaRMemisevic, title = {The Potential Energy of an Autoencoder}, author = {H Kamyshanska, R Memisevic} } @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}, author = {H Schulz, K Cho, T Raiko, S Behnke} } @misc{2014HVKoops, title = {A Deep Neural Network Approach to Automatic Birdsong Recognition}, author = {HV Koops} } @misc{2014HWang, title = {Introduction to Word2vec and its application to find predominant word senses}, author = {H Wang} } @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}, author = {I Cortes-Ciriano, Q ul Ain, V Subramanian, B Lenselink} } @misc{2014IJGoodfellowJPougetAbadieMMirzaBXu, title = {Generative Adversarial Nets}, author = {IJ Goodfellow, J Pouget-Abadie, M Mirza, B Xu} } @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}, author = {I Sutskever, O Vinyals, QV Le} } @misc{2014JASÃ¡nchezVRomeroAHToselliEVidal, title = {Icfhr2014 Competition on Handwritten Text Recognition on tranScriptorium Datasets (HTRtS)}, author = {JA SÃ¡nchez, V Romero, AH Toselli, E Vidal} } @misc{2014JAVanegasJArevaloSOtÃ¡loraFPÃ¡ez, title = {MindLab at ImageCLEF 2014: Scalable Concept Image Annotation}, author = {JA Vanegas, J Arevalo, S OtÃ¡lora, F PÃ¡ez} } @misc{2014JBohannon, title = {Helping robots see the big picture}, author = {J Bohannon} } @misc{2014JCarreiraRCaseiroJBatistaCSminchisescu, title = {Free-Form Region Description with Second-Order Pooling}, author = {J Carreira, R Caseiro, J Batista, C Sminchisescu} } @misc{2014JDoshiCMasonAWagnerZKira, title = {Deep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning}, author = {J Doshi, C Mason, A Wagner, Z Kira} } @misc{2014JDu, title = {Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition}, author = {J Du} } @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}, author = {J Jin, V Gokhale, A Dundar, B Krishnamurthy, B Martini} } @misc{2014JLedererSGuadarrama, title = {Compute Less to Get More: Using Orc to Improve Sparse Filtering}, author = {J Lederer, S Guadarrama} } @misc{2014JLiZStruzikLZhangACichocki, title = {Feature Learning from Incomplete Eeg with Denoising Autoencoder}, author = {J Li, Z Struzik, L Zhang, A Cichocki} } 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October 17, 2014 - 11:57 pm

[…] Update with 162 new papers to Deeplearning.University Bibliography by Amund Tveit. […]