Pierre Mnard
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
19
Venues
5
Active years
2017–2025
Best venue rank
A*
Where they publish
Papers
19 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback. | Cme Fiegel, Pierre Mnard, Tadashi Kozuno, Michal Valko, Vianney Perchet |
| 2024 | ICLR | Demonstration-Regularized RL. | Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Mnard |
| 2023 | ICML | Adapting to game trees in zero-sum imperfect information games. | Cme Fiegel, Pierre Mnard, Tadashi Kozuno, Rmi Munos, Vianney Perchet, Michal Valko |
| 2023 | ICML | 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 Mnard, Mohammad Gheshlaghi Azar, Rmi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvri, Wataru Kumagai, Yutaka Matsuo |
| 2023 | ICML | Fast Rates for Maximum Entropy Exploration. | Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rmi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Mnard |
| 2022 | AISTATS | Adaptive Multi-Goal Exploration. | Jean Tarbouriech, Omar Darwiche Domingues, Pierre Mnard, Matteo Pirotta, Michal Valko, Alessandro Lazaric |
| 2022 | ICML | From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. | Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Mnard |
| 2021 | AISTATS | A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces. | Omar Darwiche Domingues, Pierre Mnard, Matteo Pirotta, Emilie Kaufmann, Michal Valko |
| 2021 | ALT | Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. | Omar Darwiche Domingues, Pierre Mnard, Emilie Kaufmann, Michal Valko |
| 2021 | ALT | Adaptive Reward-Free Exploration. | Emilie Kaufmann, Pierre Mnard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko |
| 2021 | ICML | Problem Dependent View on Structured Thresholding Bandit Problems. | James Cheshire, Pierre Mnard, Alexandra Carpentier |
| 2021 | ICML | Kernel-Based Reinforcement Learning: A Finite-Time Analysis. | Omar Darwiche Domingues, Pierre Mnard, Matteo Pirotta, Emilie Kaufmann, Michal Valko |
| 2021 | ICML | Fast active learning for pure exploration in reinforcement learning. | Pierre Mnard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko |
| 2021 | ICML | UCB Momentum Q-learning: Correcting the bias without forgetting. | Pierre Mnard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko |
| 2020 | AISTATS | A single algorithm for both restless and rested rotting bandits. | Julien Seznec, Pierre Mnard, Alessandro Lazaric, Michal Valko |
| 2020 | AISTATS | Fixed-confidence guarantees for Bayesian best-arm identification. | Xuedong Shang, Rianne de Heide, Pierre Mnard, Emilie Kaufmann, Michal Valko |
| 2020 | COLT | The Influence of Shape Constraints on the Thresholding Bandit Problem. | James Cheshire, Pierre Mnard, Alexandra Carpentier |
| 2020 | ICML | Gamification of Pure Exploration for Linear Bandits. | Rmy Degenne, Pierre Mnard, Xuedong Shang, Michal Valko |
| 2017 | ALT | A minimax and asymptotically optimal algorithm for stochastic bandits. | Pierre Mnard, Aurlien Garivier |