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All publications by Hugo Larochelle
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MADE: Masked Autoencoder for Distribution Estimation
Mathieu Germain, Karol Gregor, Iain Murray and Hugo Larochelle
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Deep and Tractable Density Estimator
Benigno Uria, Iain Murray and Hugo Larochelle
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Agnostic Bayesian Learning of Ensembles
Alexandre Lacoste, Mario Marchand, François Laviolette and Hugo Larochelle
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


An Autoencoder Approach to Learning Bilingual Word Representations
Sarath P, Stanislas Lauly, Hugo Larochelle, Mitesh Khapra, Balaraman Ravindran, Vikas C. Raykar and Amrita Saha
Advances in Neural Information Processing Systems 27, 2014


RNADE: The real-valued neural autoregressive density-estimator
Benigno Uria, Iain Murray and Hugo Larochelle
Advances in Neural Information Processing Systems 26, 2013


Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek, Hugo Larochelle and Ryan P. Adams
Advances in Neural Information Processing Systems 25, 2012


A Neural Autoregressive Topic Model
Hugo Larochelle and Stanislas Lauly
Advances in Neural Information Processing Systems 25, 2012


Training Restricted Boltzmann Machines on Word Observations
George Dahl, Hugo Larochelle and Ryan P. Adams
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


On Nonparametric Guidance for Learning Autoencoder Representations
Jasper Snoek, Ryan P. Adams and Hugo Larochelle
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Learning attentional policies for tracking and recognition in video with deep networks
Loris Bazzani, Hugo Larochelle, Vittorio Murino, Jo-anne Ting and Nando D. Freitas
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


The Neural Autoregressive Distribution Estimator
Hugo Larochelle and Iain Murray
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Learning to combine foveal glimpses with a third-order Boltzmann machine
Hugo Larochelle and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 23, 2010


Efficient Learning of Deep Boltzmann Machines
Ruslan Salakhutdinov and Hugo Larochelle
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


Deep Learning using Robust Interdependent Codes
Hugo Larochelle, Dumitru Erhan 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


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


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