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Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering

Oct 21, 2020
Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour


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Supervised Seeded Iterated Learning for Interactive Language Learning

Oct 06, 2020
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron Courville


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A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning

Aug 07, 2020
Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin


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Munchausen Reinforcement Learning

Jul 28, 2020
Nino Vieillard, Olivier Pietquin, Matthieu Geist


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The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction

Jul 15, 2020
Alice Martin, Charles Ollion, Florian Strub, Sylvain Le Corff, Olivier Pietquin


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Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications

Jul 05, 2020
Sarah Perrin, Julien Perolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin


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Show me the Way: Intrinsic Motivation from Demonstrations

Jun 23, 2020
Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin


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Reinforcement Learning

Jun 13, 2020
Olivier Buffet, Olivier Pietquin, Paul Weng

* Chapter in "A Guided Tour of Artificial Intelligence Research", Springer 

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What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

Jun 10, 2020
Marcin Andrychowicz, Anton Raichuk, Piotr StaŇĄczyk, Manu Orsini, Sertan Girgin, Raphael Marinier, L√©onard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem


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Primal Wasserstein Imitation Learning

Jun 08, 2020
Robert Dadashi, Léonard Hussenot, Matthieu Geist, Olivier Pietquin


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Leverage the Average: an Analysis of Regularization in RL

Apr 10, 2020
Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist


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Countering Language Drift with Seeded Iterated Learning

Apr 06, 2020
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron Courville


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On Connections between Constrained Optimization and Reinforcement Learning

Oct 29, 2019
Nino Vieillard, Olivier Pietquin, Matthieu Geist

* Optimization Foundations of Reinforcement Learning Workshop at NeurIPS 2019 

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Self-Educated Language Agent With Hindsight Experience Replay For Instruction Following

Oct 21, 2019
Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin


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Momentum in Reinforcement Learning

Oct 21, 2019
Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist


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"I'm sorry Dave, I'm afraid I can't do that" Deep Q-learning from forbidden action

Oct 04, 2019
Mathieu Seurin, Philippe Preux, Olivier Pietquin

* Accepted at NeurIPS-2019 Workshop on Safety and Robustness in Decision Making 

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Credit Assignment as a Proxy for Transfer in Reinforcement Learning

Jul 18, 2019
Johan Ferret, Rapha√ęl Marinier, Matthieu Geist, Olivier Pietquin


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Approximate Fictitious Play for Mean Field Games

Jul 04, 2019
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin


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MULEX: Disentangling Exploitation from Exploration in Deep RL

Jul 01, 2019
Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin


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Foolproof Cooperative Learning

Jun 24, 2019
Alexis Jacq, Julien Perolat, Matthieu Geist, Olivier Pietquin


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Deep Conservative Policy Iteration

Jun 24, 2019
Nino Vieillard, Olivier Pietquin, Matthieu Geist


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Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations

May 29, 2019
Léonard Hussenot, Matthieu Geist, Olivier Pietquin


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Scaling up budgeted reinforcement learning

Mar 06, 2019
Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin

* N.Carrara and E.Leurent have equally contributed. The source code, videos and additional details for all experiments are available at https://scaling-up-brl.github.io 

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A Theory of Regularized Markov Decision Processes

Jan 31, 2019
Matthieu Geist, Bruno Scherrer, Olivier Pietquin


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Visual Reasoning with Multi-hop Feature Modulation

Oct 12, 2018
Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron Courville, Olivier Pietquin

* In Proc of ECCV 2018 

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Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Oct 08, 2018
Mel Vecerik, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin Riedmiller


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