Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Adrian Weller; Volkan Cevher (NeurIPS, 2021)

Robust Learning from Observation with Model Misspecification. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Craig Innes; Subramanian Ramamoorthy; Adrian Weller (AAMAS, 2022)

A Natural Actor-Critic Framework for Zero-Sum Markov Games. - Ahmet Alacaoglu; Luca Viano; Niao He; Volkan Cevher (ICML, 2022)

Understanding Deep Neural Function Approximation in Reinforcement Learning via $ epsilon$-Greedy Exploration. - Fanghui Liu 001; Luca Viano; Volkan Cevher (NeurIPS, 2022)

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. - Paul Rolland; Luca Viano; Norman Schürhoff; Boris Nikolov; Volkan Cevher (NeurIPS, 2022)

Proximal Point Imitation Learning. - Luca Viano; Angeliki Kamoutsi; Gergely Neu; Igor Krawczuk; Volkan Cevher (NeurIPS, 2022)

Neural NID Rules. - Luca Viano; Johanni Brea (CoRR, 2022)

Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration. - Fanghui Liu 001; Luca Viano; Volkan Cevher (CoRR, 2022)

What can online reinforcement learning with function approximation benefit from general coverage conditions? - Fanghui Liu 001; Luca Viano; Volkan Cevher (ICML, 2023)

Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. - Ioannis Panageas; Stratis Skoulakis; Luca Viano; Xiao Wang 036; Volkan Cevher (ICML, 2023)

Alternation makes the adversary weaker in two-player games. - Volkan Cevher; Ashok Cutkosky; Ali Kavis; Georgios Piliouras; Stratis Skoulakis; Luca Viano (NeurIPS, 2023)

Provable benefits of general coverage conditions in efficient online RL with function approximation. - Fanghui Liu 001; Luca Viano; Volkan Cevher (CoRR, 2023)

Imitation Learning in Discounted Linear MDPs without exploration assumptions. - Luca Viano; Stratis Skoulakis; Volkan Cevher (ICML, 2024)

Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games. - Leello Tadesse Dadi; Ioannis Panageas; Stratis Skoulakis; Luca Viano; Volkan Cevher (CoRR, 2024)

Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning. - Antoine Moulin; Gergely Neu; Luca Viano (COLT, 2025)

Best of Both Worlds: Regret Minimization versus Minimax Play. - Adrian Müller 002; Jon Schneider; Stratis Skoulakis; Luca Viano; Volkan Cevher (CoRR, 2025)

Multi-Step Alignment as Markov Games: An Optimistic Online Gradient Descent Approach with Convergence Guarantees. - Yongtao Wu; Luca Viano; Yihang Chen; Zhenyu Zhu; Kimon Antonakopoulos; Quanquan Gu; Volkan Cevher (CoRR, 2025)

IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic. - Stefano Viel; Luca Viano; Volkan Cevher (CoRR, 2025)

Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning. - Till Freihaut; Luca Viano; Volkan Cevher; Matthieu Geist; Giorgia Ramponi (CoRR, 2025)

Inverse Q-Learning Done Right: Offline Imitation Learning in Qπ-Realizable MDPs. - Antoine Moulin; Gergely Neu; Luca Viano (CoRR, 2025)