Matthieu Geist

Self-Improving Robust Preference Optimization ICLR 2025 Towards Minimax Optimality of Model-based Robust Reinforcement Learning UAI 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms NIPS 2024 Time-Constrained Robust MDPs NIPS 2024 Periodic agent-state based Q-learning for POMDPs NIPS 2024 Imitating Language via Scalable Inverse Reinforcement Learning NIPS 2024 Learning Discrete-Time Major-Minor Mean Field Games AAAI 2024 Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion EMNLP 2024 Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. ICLR 2024 On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes ICLR 2024 MusicRL: Aligning Music Generation to Human Preferences ICML 2024 Nash Learning from Human Feedback ICML 2024 Policy Gradient for Rectangular Robust Markov Decision Processes NIPS 2023 The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model NIPS 2023 Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games ICML 2023 On Imitation in Mean-field Games NIPS 2023 Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023 A Connection between One-Step RL and Critic Regularization in Reinforcement Learning ICML 2023 Extreme Q-Learning: MaxEnt RL without Entropy ICLR 2023 Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback ACL 2023 Generalization in Mean Field Games by Learning Master Policies AAAI 2022 Offline Reinforcement Learning as Anti-exploration AAAI 2022 Implicitly Regularized RL with Implicit Q-values AISTATS 2022 A general class of surrogate functions for stable and efficient reinforcement learning AISTATS 2022 Continuous Control with Action Quantization from Demonstrations ICML 2022 Large Batch Experience Replay ICML 2022 Scalable Deep Reinforcement Learning Algorithms for Mean Field Games ICML 2022 Learning Energy Networks with Generalized Fenchel-Young Losses NIPS 2022 There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning NIPS 2021 Mean Field Games Flock! The Reinforcement Learning Way IJCAI 2021 Adversarially Guided Actor-Critic ICLR 2021 Primal Wasserstein Imitation Learning ICLR 2021 What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study ICLR 2021 Learning Behaviors through Physics-driven Latent Imagination CORL 2021 Offline Reinforcement Learning with Pseudometric Learning ICML 2021 Hyperparameter Selection for Imitation Learning ICML 2021 What Matters for Adversarial Imitation Learning? NIPS 2021 Twice regularized MDPs and the equivalence between robustness and regularization NIPS 2021 Munchausen Reinforcement Learning NIPS 2020 Momentum in Reinforcement Learning AISTATS 2020 Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications NIPS 2020 Self-Attentional Credit Assignment for Transfer in Reinforcement Learning IJCAI 2020 On the Convergence of Model Free Learning in Mean Field Games AAAI 2020 Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning NIPS 2020 Deep Conservative Policy Iteration AAAI 2020 Foolproof Cooperative Learning ACML 2020 A Theory of Regularized Markov Decision Processes ICML 2019 Learning from a Learner ICML 2019 ELF: Embedded Localisation of Features in Pre-Trained CNN ICCV 2019 Reconstruct & Crush Network NIPS 2017 Is the Bellman residual a bad proxy? NIPS 2017 Softened Approximate Policy Iteration for Markov Games ICML 2016 Inverse Reinforcement Learning in Relational Domains IJCAI 2015 Approximate Modified Policy Iteration and its Application to the Game of Tetris JMLR 2015 Off-policy Learning With Eligibility Traces: A Survey JMLR 2014 Difference of Convex Functions Programming for Reinforcement Learning NIPS 2014 A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics JMLR 2013 Inverse Reinforcement Learning through Structured Classification NIPS 2012