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- Olivier Pietquin
Google DeepMind
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Publication search results
found 247 matches
- 2024
- Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl:
Learning Discrete-Time Major-Minor Mean Field Games. AAAI 2024: 9616-9625 - Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zalán Borsos, Brian McWilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Léonard Hussenot, Neil Zeghidour, Andrea Agostinelli:
MusicRL: Aligning Music Generation to Human Preferences. CoRR abs/2402.04229 (2024) - Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker:
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs. CoRR abs/2402.14740 (2024) - Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta:
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. CoRR abs/2403.03552 (2024) - Mathieu Rita, Paul Michel, Rahma Chaabouni, Olivier Pietquin, Emmanuel Dupoux, Florian Strub:
Language Evolution with Deep Learning. CoRR abs/2403.11958 (2024) - 2023
- Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour:
AudioLM: A Language Modeling Approach to Audio Generation. IEEE ACM Trans. Audio Speech Lang. Process. 31: 2523-2533 (2023) - Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor:
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. ACL (1) 2023: 6252-6272 - Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo:
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. ICML 2023: 17135-17175 - Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist:
On Imitation in Mean-field Games. NeurIPS 2023 - Chris Donahue, Antoine Caillon, Adam Roberts, Ethan Manilow, Philippe Esling, Andrea Agostinelli, Mauro Verzetti, Ian Simon, Olivier Pietquin, Neil Zeghidour, Jesse H. Engel:
SingSong: Generating musical accompaniments from singing. CoRR abs/2301.12662 (2023) - Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matthew Sharifi, Marco Tagliasacchi, Neil Zeghidour:
Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. CoRR abs/2302.03540 (2023) - Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Léonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi:
Get Back Here: Robust Imitation by Return-to-Distribution Planning. CoRR abs/2305.01400 (2023) - Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo:
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. CoRR abs/2305.13185 (2023) - Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor:
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. CoRR abs/2306.00186 (2023) - Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist:
On Imitation in Mean-field Games. CoRR abs/2306.14799 (2023) - Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl:
Learning Discrete-Time Major-Minor Mean Field Games. CoRR abs/2312.10787 (2023) - 2022
- Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin:
Generalization in Mean Field Games by Learning Master Policies. AAAI 2022: 9413-9421 - Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist:
Offline Reinforcement Learning as Anti-exploration. AAAI 2022: 8106-8114 - Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist:
Implicitly Regularized RL with Implicit Q-values. AISTATS 2022: 1380-1402 - Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie:
Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS 2022: 1557-1559 - Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin:
Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS 2022: 489-497 - Alexis Jacq, Johan Ferret, Olivier Pietquin, Matthieu Geist:
Lazy-MDPs: Towards Interpretable RL by Learning When to Act. AAMAS 2022: 669-677 - Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls:
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS 2022: 926-934 - Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin:
Scaling Mean Field Games by Online Mirror Descent. AAMAS 2022: 1028-1037 - Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux:
On the role of population heterogeneity in emergent communication. ICLR 2022 - Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin:
Continuous Control with Action Quantization from Demonstrations. ICML 2022: 4537-4557 - Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist:
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML 2022: 12078-12095 - Alice Martin, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub, Olivier Pietquin:
Learning Natural Language Generation with Truncated Reinforcement Learning. NAACL-HLT 2022: 12-37 - Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub:
Emergent Communication: Generalization and Overfitting in Lewis Games. NeurIPS 2022 - Alexis Jacq, Johan Ferret, Olivier Pietquin, Matthieu Geist:
Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act. CoRR abs/2203.08542 (2022)
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