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Efficient Learning in Non-Stationary Linear Markov Decision Processes

Oct 24, 2020
Ahmed Touati, Pascal Vincent


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Implicit Regularization in Deep Learning: A View from Function Space

Aug 03, 2020
Aristide Baratin, Thomas George, CĂ©sar Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

* 24 pages. A preliminary version of this work has been presented at the NeurIPS 2019 Workshops on "Machine Learning with Guarantees" and "Science meets Engineering of Deep Learning" 

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Stochastic Hamiltonian Gradient Methods for Smooth Games

Jul 08, 2020
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

* ICML 2020 - Proceedings of the 37th International Conference on Machine Learning 

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Sharp Analysis of Smoothed Bellman Error Embedding

Jul 07, 2020
Ahmed Touati, Pascal Vincent

* Accepted at the ICML 2020 Workshop on Theoretical Foundations of Reinforcement Learning 

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Adversarial Example Games

Jul 01, 2020
Avishek Joey Bose, Gauthier Gidel, Hugo Berrard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton


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Revisiting Loss Modelling for Unstructured Pruning

Jun 22, 2020
CĂ©sar Laurent, Camille Ballas, Thomas George, Nicolas Ballas, Pascal Vincent


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Do sequence-to-sequence VAEs learn global features of sentences?

Apr 16, 2020
Tom Bosc, Pascal Vincent


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Stable Policy Optimization via Off-Policy Divergence Regularization

Mar 09, 2020
Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent


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An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation

Jul 31, 2019
Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup


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A Closer Look at the Optimization Landscapes of Generative Adversarial Networks

Jun 11, 2019
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien


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Stochastic Neural Network with Kronecker Flow

Jun 10, 2019
Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville

* 18 pages 

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SVRG for Policy Evaluation with Fewer Gradient Evaluations

Jun 09, 2019
Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup


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Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

Feb 08, 2019
Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal


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fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

Nov 21, 2018
Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui

* 29 pages, 8 figures 

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A Variational Inequality Perspective on Generative Adversarial Networks

Nov 02, 2018
Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

* 33 pages 

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Improving Landmark Localization with Semi-Supervised Learning

Oct 28, 2018
Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Pal, Jan Kautz

* Published as a conference paper in CVPR 2018 

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Randomized Value Functions via Multiplicative Normalizing Flows

Oct 22, 2018
Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent


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Convergent Tree Backup and Retrace with Function Approximation

Oct 22, 2018
Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent


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Parametric Adversarial Divergences are Good Task Losses for Generative Modeling

Jun 27, 2018
Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

* 22 pages 

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Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis

Jun 11, 2018
Thomas George, CĂ©sar Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent


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Learning to Compute Word Embeddings On the Fly

Mar 07, 2018
Dzmitry Bahdanau, Tom Bosc, Stanisław Jastrzębski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio


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Learning to Generate Samples from Noise through Infusion Training

Mar 20, 2017
Florian Bordes, Sina Honari, Pascal Vincent

* Published as a conference paper at ICLR 2017 

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A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations

Sep 19, 2016
Alexandre de Brébisson, Pascal Vincent


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Exact gradient updates in time independent of output size for the spherical loss family

Jun 26, 2016
Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier

* Expanded journal version of our NIPS-2015 conference paper arXiv:1412.7091 with full algorithm generalized to the spherical family 

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The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family

May 27, 2016
Alexandre de Brébisson, Pascal Vincent


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Hierarchical Memory Networks

May 24, 2016
Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio

* 10 pages 

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Theano: A Python framework for fast computation of mathematical expressions

May 09, 2016
The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

* 19 pages, 5 figures 

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Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation

Apr 17, 2016
Sina Honari, Jason Yosinski, Pascal Vincent, Christopher Pal

* accepted in CVPR 2016 

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An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family

Feb 28, 2016
Alexandre de Brébisson, Pascal Vincent

* Published at ICLR 2016 

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Dropout as data augmentation

Jan 08, 2016
Xavier Bouthillier, Kishore Konda, Pascal Vincent, Roland Memisevic


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