Hugo Larochelle

Journal papers

Document Neural Autoregressive Distribution Estimation [pdf]
Stanislas Lauly, Yin Zheng, Alexandre Allauzen and Hugo Larochelle,
Journal of Machine Learning Research, 18(113): 1-24, 2017
Deep learning with coherent nanophotonic circuits [link]
Yichen Shen, Nicholas C. Harris, Scott Skirlo, Mihika Prabhu, Tom Baehr-Jones, Michael Hochberg, Xin Sun, Shijie Zhao, Hugo Larochelle, Dirk Englund and Marin Soljacic,
Nature Photonics, 2017
Movie Description [link]
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Pal, Hugo Larochelle, Aaron Courville and Bernt Schiele,
International Journal of Computer Vision, 1-27, 2017
Brain tumor segmentation with deep neural networks [link] [arXiv]
Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin and Hugo Larochelle,
Medical Image Analysis, 35: 18-31, 2017
Traffic Analytics with Low Frame Rate Videos [link]
Zhiming Luo, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li and Hugo Larochelle,
IEEE Transactions on Circuits and Systems for Video Technology, 2016
Neural Autoregressive Distribution Estimation [pdf]
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray and Hugo Larochelle,
Journal of Machine Learning Research, 17(205): 1-37, 2016
An Infinite Restricted Boltzmann Machine [pdf] [arxiv]
Marc-Alexandre Côté and Hugo Larochelle,
Neural Computation, 28(7): 1265-1288, 2016
Domain-Adversarial Training of Neural Networks [pdf]
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand and Victor Lempitsky,
Journal of Machine Learning Research, 17(59): 1-35, 2016
Correlational Neural Networks [pdf] [arxiv]
Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle and Balaraman Ravindran,
Neural Computation, 28(2): 286-304, 2016
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data [arxiv]
Yin Zheng, Yu-Jin Zhang and Hugo Larochelle,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6): 1056-1069, 2016
Within-Brain Classification for Brain Tumor Segmentation [arxiv]
Mohammad Havaei, Hugo Larochelle, Philippe Poulin and Pierre-Marc Jodoin,
International Journal of Computer Assisted Radiology and Surgery, 1-12, 2015
A Neural Autoregressive Approach to Attention-based Recognition [pdf]
Yin Zheng, Richard Zemel, Yu-Jin Zhang and Hugo Larochelle,
International Journal of Computer Vision, 113(1): 67-79, 2015
PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes [html]
Yannis J Trakadis, Caroline Buote, Jean-François Therriault, Pierre-Étienne Jacques, Hugo Larochelle and Sébastien Lévesque,
BMC Medical Genomics, 7(22), 2014
Nonparametric Guidance of Autoencoder Representations using Label Information [pdf]
Jasper Snoek, Ryan P. Adams and Hugo Larochelle,
Journal of Machine Learning Research, 13(Sep): 2567-2588, 2012
Learning Where to Attend With Deep Architectures for Image Tracking [pdf] [html]
Misha Denil, Loris Bazzani, Hugo Larochelle and Nando de Freitas,
Neural Computation, 24(8): 2151-2184, 2012
Learning Algorithms for the Classification Restricted Boltzmann Machine [pdf]
Hugo Larochelle, Michael Mandel, Razvan Pascanu and Yoshua Bengio,
Journal of Machine Learning Research, 13(Mar): 643-669, 2012
Detonation Classification from Acoustic Signature with the Restricted Boltzmann Machine [pdf]
Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Hugo Larochelle, Xavier Saint-Mleux, Christian Hudon and Jérôme Louradour,
Computational Intelligence, 28(2): 261-288, 2012
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion [pdf]
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio and Pierre-Antoine Manzagol,
Journal of Machine Learning Research, 11(Dec): 3371-3408, 2010
Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest [pdf]
Hugo Larochelle, Yoshua Bengio and Joseph Turian,
Neural Computation, 22(9): 2285-2307, 2010
Exploring Strategies for Training Deep Neural Networks [pdf]
Hugo Larochelle, Yoshua Bengio, Jérôme Louradour and Pascal Lamblin,
Journal of Machine Learning Research, 10(Jan): 1-40, 2009
Non-Local Estimation of Manifold Structure [pdf] [ps]
Yoshua Bengio, Martin Monperrus and Hugo Larochelle,
Neural Computation, 18(10): 2509-2528, 2006

Conference Papers

Transfer and Exploration via the Information Bottleneck [pdf]
Anirudh Goyal, Riashat Islam, DJ Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew Botvinick, Sergey Levine and Yoshua Bengio,
International Conference on Learning Representations, 2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning [pdf]
Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy Lillicrap, Sergey Levine, Hugo Larochelle and Yoshua Bengio,
International Conference on Learning Representations, 2019
Meta-learning for semi-supervised few-shot classification [pdf]
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua Tenenbaum, Hugo Larochelle and Richard Zemel,
International Conference on Learning Representations, 2018
A Meta-Learning Perspective on Cold-Start Recommendations for Items [pdf]
Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman and Hugo Larochelle,
Advances in Neural Information Processing Systems 30, 2017
Modulating early visual processing by language [pdf]
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin and Aaron Courville,
Advances in Neural Information Processing Systems 30, 2017
Learn to Track: Deep Learning for Tractography [pdf]
Philippe Poulin, Marc-Alexandre Cote, Jean-Christophe Houde, Laurent Petit, Peter Florian Neher, Klaus H. Maier-Hein, Hugo Larochelle and Maxime Descoteaux,
Medical Image Computing and Computer Assisted Intervention, 2017
GuessWhat?! Visual object discovery through multi-modal dialogue [pdf] [html]
Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle and Aaron Courville,
IEEE Conference on Computer Vision and Pattern Recognition, 2017
Optimization as a Model for Few-Shot Learning [pdf]
Sachin Ravi and Hugo Larochelle,
International Conference on Learning Representations, 2017
Recurrent Mixture Density Network for Spatiotemporal Visual Attention [pdf]
Loris Bazzani, Hugo Larochelle and Lorenzo Torresani,
International Conference on Learning Representations, 2017
Autoencoding beyond pixels using a learned similarity metric [pdf]
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle and Ole Winther,
International Conference on Machine Learning, 2016
Dynamic Capacity Networks [pdf]
Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle and Aaron Courville,
International Conference on Machine Learning, 2016
Describing Videos by Exploiting Temporal Structure [arxiv]
Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle and Aaron Courville,
International Conference on Computer Vision, 2015
MADE: Masked Autoencoder for Distribution Estimation [pdf] [supp]
Mathieu Germain, Karol Gregor, Iain Murray and Hugo Larochelle,
International Conference on Machine Learning, 2015
Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition [pdf]
Francis Bisson, Hugo Larochelle and Froduald Kabanza,
International Joint Conference on Artificial Intelligence, 2015
An Autoencoder Approach to Learning Bilingual Word Representations [pdf]
Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas Raykar et Amrita Saha,
Advances in Neural Information Processing Systems 27, 2014
Sequential Model-Based Ensemble Optimization [pdf]
Alexandre Lacoste, Hugo Larochelle, Mario Marchand and François Laviolette,
Uncertainty in Artificial Intelligence, 2014
Leveraging user libraries to bootstrap collaborative filtering [pdf]
Laurent Charlin, Richard Zemel and Hugo Larochelle,
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2014
Topic Modeling of Multimodal Data: an Autoregressive Approach [pdf]
Yin Zheng, Yu-Jin Zhang and Hugo Larochelle,
IEEE Conference on Computer Vision and Pattern Recognition, 2014
Efficient interactive brain tumor segmentation as within-brain kNN classification [pdf]
Mohammad Havaei, Pierre-Marc Jodoin and Hugo Larochelle,
International Conference on Pattern Recognition, 2014
A Deep and Tractable Density Estimator [pdf]
Benigno Uria, Iain Murray and Hugo Larochelle,
International Conference on Machine Learning, 2014
Agnostic Bayesian Learning of Ensembles [pdf]
Alexandre Lacoste, Mario Marchand, François Laviolette and Hugo Larochelle,
International Conference on Machine Learning, 2014
RNADE: The real-valued neural autoregressive density-estimator [pdf]
Benigno Uria, Iain Murray and Hugo Larochelle,
Advances in Neural Information Processing Systems 26, 2013
A Neural Autoregressive Topic Model [pdf] [supp] [code]
Hugo Larochelle and Stanislas Lauly,
Advances in Neural Information Processing Systems 25, 2012
Practical Bayesian Optimization of Machine Learning Algorithms [pdf] [supp] [code]
Jasper Snoek, Hugo Larochelle and Ryan P. Adams,
Advances in Neural Information Processing Systems 25, 2012
Learning to Rank By Aggregating Expert Preferences [pdf]
Maksims Volkovs, Hugo Larochelle and Richard Zemel,
International Conference on Information and Knowledge Management, 2012
Training Restricted Boltzmann Machines on Word Observations [pdf]
George E. Dahl, Ryan P. Adams and Hugo Larochelle,
International Conference on Machine Learning, 2012
On Nonparametric Guidance for Learning Autoencoder Representations [pdf]
Jasper Snoek, Ryan P. Adams and Hugo Larochelle,
Artificial Intelligence and Statistics, 2012
Classification of Sets using Restricted Boltzmann Machines [pdf] [supp] [arxiv]
Jérôme Louradour and Hugo Larochelle,
Uncertainty in Artificial Intelligence, 2011
Conditional Restricted Boltzmann Machines for Structured Output Prediction [pdf]
Volodymyr Mnih, Hugo Larochelle and Geoffrey Hinton,
Uncertainty in Artificial Intelligence, 2011
Learning Attentional Policies for Tracking and Recognition in Video with Deep Networks [pdf] [talk] [youtube]
Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino and Jo-Anne Ting,
International Conference on Machine Learning, 2011
The Neural Autoregressive Distribution Estimator [pdf] [talk] [code]
Hugo Larochelle and Iain Murray,
Artificial Intelligence and Statistics, 2011
Notable Paper Award
Learning to combine foveal glimpses with a third-order Boltzmann machine [pdf] [supp] [talk] [faces video]
Hugo Larochelle and Geoffrey Hinton,
Advances in Neural Information Processing Systems 23, 2010
Efficient Learning of Deep Boltzmann Machines [pdf][code]
Ruslan Salakhutdinov and Hugo Larochelle,
Artificial Intelligence and Statistics, 2010
Deep Learning using Robust Interdependent Codes [pdf]
Hugo Larochelle, Dumitru Erhan and Pascal Vincent,
Artificial Intelligence and Statistics, 2009
Classification using Discriminative Restricted Boltzmann Machines [pdf] [talk]
Hugo Larochelle and Yoshua Bengio,
International Conference on Machine Learning, 2008
Extracting and Composing Robust Features with Denoising Autoencoders [pdf]
Pascal Vincent, Hugo Larochelle, Yoshua Bengio and Pierre-Antoine Manzagol,
International Conference on Machine Learning, 2008
Zero-data Learning of New Tasks [pdf]
Hugo Larochelle, Dumitru Erhan and Yoshua Bengio,
AAAI Conference on Artificial Intelligence, 2008
An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation [pdf][html]
Hugo Larochelle, Dumitru Erhan, Aaron Courville, James Bergstra and Yoshua Bengio,
International Conference on Machine Learning, 2007
Greedy Layer-Wise Training of Deep Networks [pdf]
Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle,
Advances in Neural Information Processing Systems 19, 2007
Non-Local Manifold Parzen Windows [pdf]
Yoshua Bengio, Hugo Larochelle and Pascal Vincent,
Advances in Neural Information Processing Systems 18, 2006

Thesis

Études de techniques d'appentissage non-supervisé pour l'amélioration de l'entraînement supervisé de modèles connexionnistes [pdf]
Hugo Larochelle,
Ph.D. thesis, Université de Montréal, 2009

Workshop Papers and Technical Reports

An Infinite Restricted Boltzmann Machine [arxiv]
Marc-Alexandre Côté and Hugo Larochelle,
arXiv, 2015
Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research [arxiv]
Atousa Torabi, Christopher Pal, Hugo Larochelle and Aaron Courville,
arXiv, 2015
Learning Multilingual Word Representations using a Bag-of-Words Autoencoder [pdf] [arxiv]
Stanislas Lauly, Alex Boulanger and Hugo Larochelle,
NIPS Deep Learning Workshop, 2013
Loss-sensitive Training of Probabilistic Conditional Random Fields [arxiv]
Maksims Volkovs, Hugo Larochelle and Richard Zemel,
arXiv, 2011
Autotagging music with conditional restricted Boltzmann machines [arxiv]
Michael Mandel, Razvan Pascanu, Hugo Larochelle and Yoshua Bengio,
arXiv, 2011
Extracting and Composing Robust Features with Denoising Autoencoders [pdf]
Pascal Vincent, Hugo Larochelle, Yoshua Bengio and Pierre-Antoine Manzagol,
Technical Report #1316, Département d'informatique et recherche opérationnelle,
Université de Montréal, 2008
Distributed Representation Prediction for Generalization to New Words [pdf]
Hugo Larochelle and Yoshua Bengio,
Technical Report #1284, Département d'informatique et recherche opérationnelle,
Université de Montréal, 2006
Greedy Layer-Wise Training of Deep Networks [pdf]
Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle,
Technical Report #1282, Département d'informatique et recherche opérationnelle,
Université de Montréal, 2006
Non-Local Manifold Parzen Windows [pdf] [ps]
Yoshua Bengio and Hugo Larochelle,
Technical Report #1264, Département d'informatique et recherche opérationnelle,
Université de Montréal, 2005

Others

Classification using Discriminative Restricted Boltzmann Machines [pdf]
Hugo Larochelle and Yoshua Bengio,
MITACS Second Canada-France Congress,
Third place at poster competition,
Montreal, Canada, 2008
Deep Woods [pdf]
Yoshua Bengio, Hugo Larochelle and Joseph Turian,
Poster presented at the Learning@Snowbird Workshop,
Snowbird, USA, 2008
Generalization to a zero-data task: an empirical study [pdf] [ps]
Hugo Larochelle, Dumitru Erhan and Yoshua Bengio
Talk and poster presented at the Learning Workshop,
San Juan, Puerto Rico, 2007
Didactiel sur les réseaux de neurones en traitement de la langue [pdf]
Hugo Larochelle,
Talk in the RALI-OLST seminar series
Université de Montréal, 2006
Non-Local Manifold Parzen Windows [pdf]
Yoshua Bengio, Hugo Larochelle and Pascal Vincent,
Talk at the CIAR Summer School,
University of Toronto, 2005
Non-Local Manifold Parzen Windows [pdf] [ps]
Yoshua Bengio and Hugo Larochelle,
Poster presented at the Learning@Snowbird Workshop,
Snowbird, USA, 2005
Implantation et analyse d’un modèle graphique de désambiguïsation
à entraînement supervisé, semi-supervisé et non-supervisé [pdf] [ps]
Hugo Larochelle and Yoshua Bengio,
IFT3051 project, Département d'informatique et recherche opérationnelle,
Université de Montréal, 2004.
Some Supervised Models in Disambiguation [ppt]
Hugo Larochelle, Christian Jauvin and Yoshua Bengio,
Poster presented at MITACS Quebec Interchange,
Montréal, Canada, 2003.
Étude de la pertinence de métriques statistiques pour la détection de termes dans un document [pdf] [ps]
Hugo Larochelle and Philippe Langlais,
NSERC Internship report at RALI lab,
Département d'informatique et recherche opérationnelle,
Université de Montréal, été 2002.