Pietquin, Olivier

59 publications

ICLR 2025 NatureLM-Audio: An Audio-Language Foundation Model for Bioacoustics David Robinson, Marius Miron, Masato Hagiwara, Olivier Pietquin

ICLR 2025 Self-Improving Robust Preference Optimization Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi Azar

NeurIPS 2025 ShiQ: Bringing Back Bellman to LLMs Pierre Clavier, Nathan Grinsztajn, Raphaël Avalos, Yannis Flet-Berliac, Irem Ergun, Omar Darwiche Domingues, Olivier Pietquin, Pierre Harvey Richemond, Florian Strub, Matthieu Geist

AAAI 2024 Learning Discrete-Time Major-Minor Mean Field Games Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl

ICML 2024 MusicRL: Aligning Music Generation to Human Preferences Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zalán Borsos, Brian Mcwilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Leonard Hussenot, Neil Zeghidour, Andrea Agostinelli

NeurIPS 2023 On Imitation in Mean-Field Games Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Lauriere, Matthieu Geist

NeurIPSW 2023 On the Importance of Data Collection for Training General Goal-Reaching Policies. Alexis D. Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem

ICML 2023 Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Menard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo

AISTATS 2022 Implicitly Regularized RL with Implicit Q-Values Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist

ICML 2022 Continuous Control with Action Quantization from Demonstrations Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

NeurIPS 2022 Emergent Communication: Generalization and Overfitting in Lewis Games Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub

AAAI 2022 Generalization in Mean Field Games by Learning Master Policies Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin

AAAI 2022 Offline Reinforcement Learning as Anti-Exploration Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist

ICLR 2022 On the Role of Population Heterogeneity in Emergent Communication Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux

ICML 2022 Scalable Deep Reinforcement Learning Algorithms for Mean Field Games Mathieu Lauriere, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Perolat, Romuald Elie, Olivier Pietquin, Matthieu Geist

ICLR 2021 Adversarially Guided Actor-Critic Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist

NeurIPSW 2021 Continuous Control with Action Quantization from Demonstrations Robert Dadashi, Leonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

IJCAI 2021 Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin

ICML 2021 Hyperparameter Selection for Imitation Learning Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin

NeurIPSW 2021 Implicitly Regularized RL with Implicit Q-Values Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist

IJCAI 2021 Mean Field Games Flock! the Reinforcement Learning Way Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin

ICML 2021 Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist

ICLR 2021 Primal Wasserstein Imitation Learning Robert Dadashi, Leonard Hussenot, Matthieu Geist, Olivier Pietquin

NeurIPS 2021 There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist

NeurIPS 2021 What Matters for Adversarial Imitation Learning? Manu Orsini, Anton Raichuk, Leonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz

ICLR 2021 What Matters for On-Policy Deep Actor-Critic Methods? a Large-Scale Study Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Leonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem

ICML 2020 Countering Language Drift with Seeded Iterated Learning Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, Olivier Pietquin

AAAI 2020 Deep Conservative Policy Iteration Nino Vieillard, Olivier Pietquin, Matthieu Geist

NeurIPS 2020 Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications Sarah Perrin, Julien Perolat, Mathieu Lauriere, Matthieu Geist, Romuald Elie, Olivier Pietquin

ACML 2020 Foolproof Cooperative Learning Alexis Jacq, Julien Perolat, Matthieu Geist, Olivier Pietquin

NeurIPS 2020 Leverage the Average: An Analysis of KL Regularization in Reinforcement Learning Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Remi Munos, Matthieu Geist

AISTATS 2020 Momentum in Reinforcement Learning Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist

NeurIPS 2020 Munchausen Reinforcement Learning Nino Vieillard, Olivier Pietquin, Matthieu Geist

AAAI 2020 On the Convergence of Model Free Learning in Mean Field Games Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin

IJCAI 2020 Self-Attentional Credit Assignment for Transfer in Reinforcement Learning Johan Ferret, Raphaël Marinier, Matthieu Geist, Olivier Pietquin

ICML 2019 A Theory of Regularized Markov Decision Processes Matthieu Geist, Bruno Scherrer, Olivier Pietquin

NeurIPS 2019 Budgeted Reinforcement Learning in Continuous State Space Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin

ICML 2019 Learning from a Learner Alexis Jacq, Matthieu Geist, Ana Paiva, Olivier Pietquin

AISTATS 2018 Actor-Critic Fictitious Play in Simultaneous Move Multistage Games Julien Pérolat, Bilal Piot, Olivier Pietquin

AAAI 2018 Deep Q-Learning from Demonstrations Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys

ICLR 2018 Noisy Networks for Exploration Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Remi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

IJCAI 2017 End-to-End Optimization of Goal-Driven and Visually Grounded Dialogue Systems Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin

CVPR 2017 GuessWhat?! Visual Object Discovery Through Multi-Modal Dialogue Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron Courville

NeurIPS 2017 Is the Bellman Residual a Bad Proxy? Matthieu Geist, Bilal Piot, Olivier Pietquin

AISTATS 2017 Learning Nash Equilibrium for General-Sum Markov Games from Batch Data Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin

NeurIPS 2017 Modulating Early Visual Processing by Language Harm de Vries, Florian Strub, Jeremie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville

AISTATS 2016 On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin

ICML 2016 PAC Learning of Probabilistic Automaton Based on the Method of Moments Hadrien Glaude, Olivier Pietquin

ICML 2016 Softened Approximate Policy Iteration for Markov Games Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin

ICML 2015 Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games Julien Perolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin

IJCAI 2015 Inverse Reinforcement Learning in Relational Domains Thibaut Munzer, Bilal Piot, Matthieu Geist, Olivier Pietquin, Manuel Lopes

ECML-PKDD 2014 Boosted Bellman Residual Minimization Handling Expert Demonstrations Bilal Piot, Matthieu Geist, Olivier Pietquin

NeurIPS 2014 Difference of Convex Functions Programming for Reinforcement Learning Bilal Piot, Matthieu Geist, Olivier Pietquin

ECML-PKDD 2013 A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin

IJCAI 2013 Inverse Reinforcement Learning for Interactive Systems Olivier Pietquin

ECML-PKDD 2013 Learning from Demonstrations: Is It Worth Estimating a Reward Function? Bilal Piot, Matthieu Geist, Olivier Pietquin

NeurIPS 2012 Inverse Reinforcement Learning Through Structured Classification Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin

IJCAI 2011 Sample Efficient On-Line Learning of Optimal Dialogue Policies with Kalman Temporal Differences Olivier Pietquin, Matthieu Geist, Senthilkumar Chandramohan

JAIR 2010 Kalman Temporal Differences Matthieu Geist, Olivier Pietquin