Deep Learning Embeddings for Discontinuous Linguistic Units
Wenpeng Yin; Hinrich Schütze
Learning Factored Representations in a Deep Mixture of Experts
David Eigen; Marc'Aurelio Ranzato; Ilya Sutskever
Learning Information Spread in Content Networks
Cédric Lagnier; Simon Bourigault; Sylvain Lamprier; Ludovic Denoyer; Patrick Gallinari
Learning States Representations in POMDP
Gabriella Contardo; Ludovic Denoyer; Thierry Artieres; Patrick Gallinari
Distributional Models and Deep Learning Embeddings: Combining the Best of Both Worlds
Irina Sergienya; Hinrich Schütze
Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Mathias Berglund; Tapani Raiko
Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error
David Buchaca; Enrique Romero; Ferran Mazzanti; Jordi Delgado
Continuous Learning: Engineering Super Features With Feature Algebras
Michael Tetelman
Multimodal Transitions for Generative Stochastic Networks
Sherjil Ozair; Li Yao; Yoshua Bengio
Factorial Hidden Markov Models for Learning Representations of Natural Language
Anjan Nepal; Alexander Yates
Can recursive neural tensor networks learn logical reasoning?
Samuel R. Bowman
A Primal-Dual Method for Training Recurrent Neural Networks Constrained by the Echo-State Property
Jianshu Chen; Li Deng
Dimitrios Athanasakis; John Shawe-Taylor; Delmiro Fernandez-Reyes
Rate-Distortion Auto-Encoders
Luis G. Sanchez Giraldo; Jose C. Principe
Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks
Andrew Davis; Itamar Arel
Semistochastic Quadratic Bound Methods
Aleksandr Y. Aravkin; Anna Choromanska; Tony Jebara; Dimitri Kanevsky
An Architecture for Distinguishing between Predictors and Inhibitors in Reinforcement Learning
Relaxations for inference in restricted Boltzmann machines
Sida I. Wang; Roy Frostig; Percy Liang; Christopher D. Manning
Learning Semantic Script Knowledge with Event Embeddings
Ashutosh Modi; Ivan Titov
Unsupervised Feature Learning by Deep Sparse Coding
Yunlong He; Koray Kavukcuoglu; Yun Wang; Arthur Szlam; Yanjun Qi
End-to-End Text Recognition with Hybrid HMM Maxout Models
Ouais Alsharif; Joelle Pineau
Multi-GPU Training of ConvNets
Omry Yadan; Keith Adams; Yaniv Taigman; Marc'Aurelio Ranzato
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
Thomas Huang; Zhe Lin; Hailin Jin; Jianchao Yang; Thomas Paine
Generic Deep Networks with Wavelet Scattering
Edouard Oyallon; Stéphane Mallat; Laurent Sifre
Deep learning for class-generic object detection
Brody Huval; Adam Coates; Andrew Ng
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan; Andrea Vedaldi; Andrew Zisserman
Unsupervised feature learning by augmenting single images
Alexey Dosovitskiy; Jost Tobias Springenberg; Thomas Brox
Correlation-based construction of neighborhood and edge features
Balázs Kégl
Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines
Nan Wang; Laurenz Wiskott; Dirk Jancke
Understanding Deep Architectures using a Recursive Convolutional Network
David Eigen; Jason Rolfe; Rob Fergus; Yann LeCun
Learning High-level Image Representation for Image Retrieval via Multi-Task DNN using Clickthrough Data
Wei Yu; Tiejun Zhao; Yalong Bai; Wei-Ying Ma; Kuiyuan Yang
One-Shot Adaptation of Supervised Deep Convolutional Models
Judy Hoffman; Eric Tzeng; Jeff Donahue; Yangqing Jia; Kate Saenko; Trevor Darrell
Improving Deep Neural Networks with Probabilistic Maxout Units
Jost Tobias Springenberg; Martin Riedmiller
Efficient Visual Coding: From Retina To V2
Honghao Shan; Garrison Cottrell
Deep learning for neuroimaging: a validation study
Sergey M. Plis; Devon R. Hjelm; Ruslan Salakhutdinov; Vince D. Calhoun
Image Representation Learning Using Graph Regularized Auto-Encoders
Yiyi Liao; Yue Wang; Yong Liu
Deep Belief Networks for Image Denoising
Mohammad Ali Keyvanrad; Mohammad Pezeshki; Mohammad Mehdi Homayounpour
Approximated Infomax Early Stopping: Revisiting Gaussian RBMs on Natural Images
Taichi Kiwaki; Takaki Makino; Kazuyuki Aihara
