Marco Mussi

Gym4ReaL: Towards Real-World Reference Environments for Reinforcement Learning

Tightening Regret Lower and Upper Bounds in Restless Rising Bandits

Generalized Kernelized Bandits: Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds

Sleeping Reinforcement Learning

Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity

Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback

No-regret Learning with Revealed Transitions in Adversarial Markov Decision Processes