Dadashi, Robert

13 publications

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

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

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

AAAI 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver

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

NeurIPS 2019 A Geometric Perspective on Optimal Representations for Reinforcement Learning Marc Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle

ICML 2019 Statistics and Samples in Distributional Reinforcement Learning Mark Rowland, Robert Dadashi, Saurabh Kumar, Remi Munos, Marc G. Bellemare, Will Dabney

ICML 2019 The Value Function Polytope in Reinforcement Learning Robert Dadashi, Adrien Ali Taiga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare