Azar, Mohammad Gheshlaghi

23 publications

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

JMLR 2024 An Analysis of Quantile Temporal-Difference Learning Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney

NeurIPSW 2022 BLaDE: Robust Exploration via Diffusion Models Bilal Piot, Zhaohan Daniel Guo, Shantanu Thakoor, Mohammad Gheshlaghi Azar

NeurIPS 2022 BYOL-Explore: Exploration by Bootstrapped Prediction Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Avila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Remi Munos, Mohammad Gheshlaghi Azar, Bilal Piot

ICLR 2022 Large-Scale Representation Learning on Graphs via Bootstrapping Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L Dyer, Remi Munos, Petar Veličković, Michal Valko

ICLRW 2021 Bootstrapped Representation Learning on Graphs Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Remi Munos, Petar Veličković, Michal Valko

NeurIPS 2021 Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith Hengen, Michal Valko, Eva Dyer

ICML 2020 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Zhaohan Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Remi Munos, Mohammad Gheshlaghi Azar

NeurIPS 2020 Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Remi Munos, Michal Valko

ICML 2020 Fast Computation of Nash Equilibria in Imperfect Information Games Remi Munos, Julien Perolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls

NeurIPS 2019 Hindsight Credit Assignment Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Gheshlaghi Azar, Bilal Piot, Nicolas Heess, Hado P van Hasselt, Gregory Wayne, Satinder Singh, Doina Precup, Remi Munos

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

AAAI 2018 Rainbow: Combining Improvements in Deep Reinforcement Learning Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver

ICLR 2018 The Reactor: A Fast and Sample-Efficient Actor-Critic Agent for Reinforcement Learning Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar, Bilal Piot, Marc Bellemare, Remi Munos

ICML 2017 Minimax Regret Bounds for Reinforcement Learning Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos

UAI 2016 Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes Mohammad Gheshlaghi Azar, Eva L. Dyer, Konrad P. Körding

ICML 2014 Online Stochastic Optimization Under Correlated Bandit Feedback Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

MLJ 2013 Minimax PAC Bounds on the Sample Complexity of Reinforcement Learning with a Generative Model Mohammad Gheshlaghi Azar, Rémi Munos, Hilbert J. Kappen

ECML-PKDD 2013 Regret Bounds for Reinforcement Learning with Policy Advice Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

NeurIPS 2013 Sequential Transfer in Multi-Armed Bandit with Finite Set of Models Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

JMLR 2012 Dynamic Policy Programming Mohammad Gheshlaghi Azar, Vicenç Gómez, Hilbert J. Kappen

ICML 2012 On the Sample Complexity of Reinforcement Learning with a Generative Model Mohammad Gheshlaghi Azar, Rémi Munos, Bert Kappen

AISTATS 2011 Dynamic Policy Programming with Function Approximation Mohammad Gheshlaghi Azar, Vicenç Gómez, Bert Kappen