Search Machine Learning Repository:
All publications by Yoshua Bengio
authors venues years



Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel and Yoshua Bengio
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Stephan Gouws, Yoshua Bengio and Greg Corrado
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Gated Feedback Recurrent Neural Networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho and Yoshua Bengio
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Equilibrated adaptive learning rates for non-convex optimization
Yann Dauphin, Harm D. Vries and Yoshua Bengio
Advances in Neural Information Processing Systems 28, 2015


Attention-Based Models for Speech Recognition
Jan K. Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho and Yoshua Bengio
Advances in Neural Information Processing Systems 28, 2015


A Recurrent Latent Variable Model for Sequential Data
Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville and Yoshua Bengio
Advances in Neural Information Processing Systems 28, 2015


BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio and Jean-pierre David
Advances in Neural Information Processing Systems 28, 2015


Marginalized Denoising Auto-encoders for Nonlinear Representations
Minmin Chen, Kilian Q. Weinberger, Fei Sha and Yoshua Bengio
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio, Eric Laufer, Guillaume Alain and Jason Yosinski
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli and Yoshua Bengio
Advances in Neural Information Processing Systems 27, 2014


Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-abadie, Mehdi Mirza, Bing Xu, David Warde-farley, Sherjil Ozair, Aaron Courville and Yoshua Bengio
Advances in Neural Information Processing Systems 27, 2014


On the Number of Linear Regions of Deep Neural Networks
Guido F. Montufar, Razvan Pascanu, Kyunghyun Cho and Yoshua Bengio
Advances in Neural Information Processing Systems 27, 2014


How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio and Hod Lipson
Advances in Neural Information Processing Systems 27, 2014


Iterative Neural Autoregressive Distribution Estimator NADE-k
Tapani Raiko, Yao Li, Kyunghyun Cho and Yoshua Bengio
Advances in Neural Information Processing Systems 27, 2014


On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov and Yoshua Bengio
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Maxout Networks
Ian Goodfellow, David Warde-farley, Mehdi Mirza, Aaron Courville and Yoshua Bengio
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Multi-Prediction Deep Boltzmann Machines
Ian Goodfellow, Mehdi Mirza, Aaron Courville and Yoshua Bengio
Advances in Neural Information Processing Systems 26, 2013


Generalized Denoising Auto-Encoders as Generative Models
Yoshua Bengio, Li Yao, Guillaume Alain and Pascal Vincent
Advances in Neural Information Processing Systems 26, 2013


Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs
Yann Dauphin and Yoshua Bengio
Advances in Neural Information Processing Systems 26, 2013


Better Mixing via Deep Representations
Yoshua Bengio, Gregoire Mesnil, Yann Dauphin and Salah Rifai
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


A Generative Process for sampling Contractive Auto-Encoders
Salah Rifai, Yoshua Bengio, Pascal Vincent and Yann N. Dauphin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Large-Scale Feature Learning With Spike-and-Slab Sparse Coding
Ian Goodfellow, Yoshua Bengio and Aaron C. Courville
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription
Nicolas Boulanger-lewandowski, Yoshua Bengio and Pascal Vincent
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
Antoine Bordes, Xavier Glorot, Jason Weston and Yoshua Bengio
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Algorithms for Hyper-Parameter Optimization
James S. Bergstra, Rémi Bardenet, Yoshua Bengio and Balázs Kégl
Advances in Neural Information Processing Systems 24, 2011


On Tracking The Partition Function
Guillaume Desjardins, Yoshua Bengio and Aaron C. Courville
Advances in Neural Information Processing Systems 24, 2011


The Manifold Tangent Classifier
Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio and Xavier Muller
Advances in Neural Information Processing Systems 24, 2011


Shallow vs. Deep Sum-Product Networks
Olivier Delalleau and Yoshua Bengio
Advances in Neural Information Processing Systems 24, 2011


Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot and Yoshua Bengio
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach
Xavier Glorot, Antoine Bordes and Yoshua Bengio
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Large-Scale Learning of Embeddings with Reconstruction Sampling
Xavier Glorot, Yoshua Bengio and Yann N. Dauphin
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Unsupervised Models of Images by Spike-and-Slab RBMs
Yoshua Bengio, Aaron C. Courville and James S. Bergstra
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Deep Sparse Rectifier Neural Networks
Xavier Glorot, Antoine Bordes and Yoshua Bengio
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


A Spike and Slab Restricted Boltzmann Machine
Aaron C. Courville, James Bergstra and Yoshua Bengio
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Deep Learners Benefit More from Out-of-Distribution Examples
Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger-lewandowski, Thomas M. Breuel, Youssouf Chherawala, Moustapha Cisse, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain P. Lebeuf, Razvan Pascanu, Salah Rifai, Françcois Savard and Guillaume Sicard
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Discussion of "The Neural Autoregressive Distribution Estimator"
Yoshua Bengio
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Why Does Unsupervised Pre-training Help Deep Learning?
Dumitru Erhan, Aaron C. Courville, Yoshua Bengio and Pascal Vincent
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent and Olivier Delalleau
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Exploring Strategies for Training Deep Neural Networks
Hugo Larochelle, Yoshua Bengio, Jérôme Louradour and Pascal Lamblin
Journal of Machine Learning Research, 2009


Incorporating Functional Knowledge in Neural Networks
Charles Dugas, Yoshua Bengio, Françcois Bélisle, Claude Nadeau and René Garcia
Journal of Machine Learning Research, 2009


Workshop summary: Workshop on learning feature hierarchies
Kay Yu, Ruslan Salakhutdinov, Yann Lecun, Geoffrey E. Hinton and Yoshua Bengio
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert and Jason Weston
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism
Douglas Eck, Yoshua Bengio and Aaron C. Courville
Advances in Neural Information Processing Systems 22, 2009


Slow, Decorrelated Features for Pretraining Complex Cell-like Networks
Yoshua Bengio and James S. Bergstra
Advances in Neural Information Processing Systems 22, 2009


The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training
Dumitru Erhan, Pierre-antoine Manzagol, Yoshua Bengio, Samy Bengio and Pascal Vincent
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio and Pierre-antoine Manzagol
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Classification using discriminative restricted Boltzmann machines
Hugo Larochelle and Yoshua Bengio
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


An empirical evaluation of deep architectures on problems with many factors of variation
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra and Yoshua Bengio
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Learning the 2-D Topology of Images
Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau and Balázs Kégl
Advances in Neural Information Processing Systems 20, 2007


Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
Nicolas Chapados and Yoshua Bengio
Advances in Neural Information Processing Systems 20, 2007


Topmoumoute Online Natural Gradient Algorithm
Nicolas L. Roux, Pierre-antoine Manzagol and Yoshua Bengio
Advances in Neural Information Processing Systems 20, 2007


Continuous Neural Networks
Nicolas L. Roux and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data
Julie Carreau and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Greedy Layer-Wise Training of Deep Networks
Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle
Advances in Neural Information Processing Systems 19, 2006


Convex Neural Networks
Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau and Patrice Marcotte
Advances in Neural Information Processing Systems 18, 2005


Non-Local Manifold Parzen Windows
Yoshua Bengio, Hugo Larochelle and Pascal Vincent
Advances in Neural Information Processing Systems 18, 2005


The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau and Nicolas L. Roux
Advances in Neural Information Processing Systems 18, 2005


Non-Local Manifold Tangent Learning
Yoshua Bengio and Martin Monperrus
Advances in Neural Information Processing Systems 17, 2004


Brain Inspired Reinforcement Learning
Françcois Rivest, Yoshua Bengio and John Kalaska
Advances in Neural Information Processing Systems 17, 2004


Semi-supervised Learning by Entropy Minimization
Yves Grandvalet and Yoshua Bengio
Advances in Neural Information Processing Systems 17, 2004


No Unbiased Estimator of the Variance of K-Fold Cross-Validation
Yoshua Bengio and Yves Grandvalet
Journal of Machine Learning Research, 2004


No Unbiased Estimator of the Variance of K-Fold Cross-Validation
Yoshua Bengio and Yves Grandvalet
Advances in Neural Information Processing Systems 16, 2003


Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Yoshua Bengio, Jean-françcois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas L. Roux and Marie Ouimet
Advances in Neural Information Processing Systems 16, 2003


A Neural Probabilistic Language Model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent and Christian Janvin
Journal of Machine Learning Research, 2003


Extensions to Metric-Based Model Selection
Yoshua Bengio and Nicolas Chapados
Journal of Machine Learning Research, 2003


Manifold Parzen Windows
Pascal Vincent and Yoshua Bengio
Advances in Neural Information Processing Systems 15, 2002


K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
Pascal Vincent and Yoshua Bengio
Advances in Neural Information Processing Systems 14, 2001


A Parallel Mixture of SVMs for Very Large Scale Problems
Ronan Collobert, Samy Bengio and Yoshua Bengio
Advances in Neural Information Processing Systems 14, 2001