3 papers
cs.AI2026
Minimax Optimal Variance-Aware Regret Bounds for Multinomial Logistic MDPs
Pierre Boudart, Pierre Gaillard, Alessandro Rudi
We study reinforcement learning for episodic Markov Decision Processes (MDPs) whose transitions are modelled by a multinomial logistic (MNL) model. Existing algorithms for MNL mixt…
stat.ML2025
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
Pierre Boudart, Pierre Gaillard, Alessandro Rudi
We consider the multinomial logistic bandit problem in which a learner interacts with an environment by selecting actions to maximize expected rewards based on probabilistic feedba…
cs.LG2024
Structured Prediction in Online Learning
Pierre Boudart, Alessandro Rudi, Pierre Gaillard
We study a theoretical and algorithmic framework for structured prediction in the online learning setting. The problem of structured prediction, i.e. estimating function where the…