Luca Viano

CoRR, May, 2025

Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning.

[BibT_eX]

[DOI]

CoRR, May, 2025

Multi-Step Alignment as Markov Games: An Optimistic Online Gradient Descent Approach with Convergence Guarantees.

[BibT_eX]

[DOI]

CoRR, February, 2025

IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic.

[BibT_eX]

[DOI]

Stefano Viel

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Best of Both Worlds: Regret Minimization versus Minimax Play.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning.

[BibT_eX]

[DOI]

Antoine Moulin

Gergely Neu

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games.

[BibT_eX]

[DOI]

CoRR, 2024

Convergence to Equilibrium of No-Regret Dynamics in Congestion Games.

[BibT_eX]

[DOI]

Proceedings of the Web and Internet Economics - 20th International Conference, 2024

Imitation Learning in Discounted Linear MDPs without exploration assumptions.

[BibT_eX]

[DOI]

Stratis Skoulakis

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Provable benefits of general coverage conditions in efficient online RL with function approximation.

[BibT_eX]

[DOI]

CoRR, 2023

Alternation makes the adversary weaker in two-player games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

What can online reinforcement learning with function approximation benefit from general coverage conditions?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration.

[BibT_eX]

[DOI]

CoRR, 2022

Neural NID Rules.

[BibT_eX]

[DOI]

Johanni Brea

CoRR, 2022

Proximal Point Imitation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Natural Actor-Critic Framework for Zero-Sum Markov Games.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Robust Learning from Observation with Model Misspecification.

[BibT_eX]

[DOI]

Yu-Ting Huang

Parameswaran Kamalaruban

Craig Innes

Subramanian Ramamoorthy

Adrian Weller

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch.

[BibT_eX]

[DOI]

Yu-Ting Huang

Parameswaran Kamalaruban

Adrian Weller