Geist, Matthieu

78 publications

NeurIPS 2025 Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning Till Freihaut, Luca Viano, Volkan Cevher, Matthieu Geist, Giorgia Ramponi

TMLR 2025 RoboRAN: A Unified Robotics Framework for Reinforcement Learning-Based Autonomous Navigation Matteo El-Hariry, Antoine Richard, Ricard Marsal, Luis Felipe Wolf Batista, Matthieu Geist, Cédric Pradalier, Miguel Olivares-Mendez

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

TMLR 2024 A Survey of Temporal Credit Assignment in Deep Reinforcement Learning Eduardo Pignatelli, Johan Ferret, Matthieu Geist, Thomas Mesnard, Hado van Hasselt, Laura Toni

ICLR 2024 Closing the Gap Between TD Learning and Supervised Learning - A Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

NeurIPS 2024 Imitating Language via Scalable Inverse Reinforcement Learning Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin Riedmiller

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

ICML 2024 Nash Learning from Human Feedback Remi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Côme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J Mankowitz, Doina Precup, Bilal Piot

NeurIPS 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist

ICLR 2024 On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem

NeurIPS 2024 Periodic Agent-State Based Q-Learning for POMDPs Amit Sinha, Matthieu Geist, Aditya Mahajan

NeurIPS 2024 Time-Constrained Robust MDPs Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson

UAI 2024 Towards Minimax Optimality of Model-Based Robust Reinforcement Learning Pierre Clavier, Erwan Le Pennec, Matthieu Geist

ICML 2023 A Connection Between One-Step RL and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

NeurIPSW 2023 Closing the Gap Between TD Learning and Supervised Learning -- a Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

NeurIPSW 2023 Closing the Gap Between TD Learning and Supervised Learning -- a Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

ICLR 2023 Extreme Q-Learning: MaxEnt RL Without Entropy Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon

ECML-PKDD 2023 Offline Reinforcement Learning with On-Policy Q-Function Regularization Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist

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

NeurIPS 2023 Policy Gradient for Rectangular Robust Markov Decision Processes Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Y. Levy, Shie Mannor

ICML 2023 Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games Batuhan Yardim, Semih Cayci, Matthieu Geist, Niao He

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

NeurIPSW 2023 Robustness and Regularization in Reinforcement Learning Esther Derman, Yevgeniy Men, Matthieu Geist, Shie Mannor

NeurIPS 2023 The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi

AISTATS 2022 A General Class of Surrogate Functions for Stable and Efficient Reinforcement Learning Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

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

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

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

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

ICML 2022 Large Batch Experience Replay Thibault Lahire, Matthieu Geist, Emmanuel Rachelson

NeurIPS 2022 Learning Energy Networks with Generalized Fenchel-Young Losses Mathieu Blondel, Felipe Llinares-Lopez, Robert Dadashi, Leonard Hussenot, Matthieu Geist

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

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

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

CoRL 2021 Learning Behaviors Through Physics-Driven Latent Imagination Antoine Richard, Stéphanie Aravecchia, Matthieu Geist, Cédric Pradalier

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 Twice Regularized MDPs and the Equivalence Between Robustness and Regularization Esther Derman, Matthieu Geist, Shie Mannor

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

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

ECML-PKDD 2020 Filling Gaps in Micro-Meteorological Data Antoine Richard, Lior Fine, Offer Rozenstein, Josef Tanny, Matthieu Geist, Cédric Pradalier

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

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

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

NeurIPS 2017 Reconstruct & Crush Network Erinc Merdivan, Mohammad Reza Loghmani, Matthieu Geist

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

JMLR 2015 Approximate Modified Policy Iteration and Its Application to the Game of Tetris Bruno Scherrer, Mohammad Ghavamzadeh, Victor Gabillon, Boris Lesner, Matthieu Geist

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

MLJ 2015 Soft-Max Boosting Matthieu Geist

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 2014 Local Policy Search in a Convex Space and Conservative Policy Iteration as Boosted Policy Search Bruno Scherrer, Matthieu Geist

JMLR 2014 Off-Policy Learning with Eligibility Traces: A Survey Matthieu Geist, Bruno Scherrer

MLOSS 2013 A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics Hervé Frezza-Buet, Matthieu Geist

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

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

ICML 2012 A Dantzig Selector Approach to Temporal Difference Learning Matthieu Geist, Bruno Scherrer, Alessandro Lazaric, Mohammad Ghavamzadeh

ICML 2012 Approximate Modified Policy Iteration Bruno Scherrer, Victor Gabillon, Mohammad Ghavamzadeh, Matthieu Geist

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