4 papers
Minimax PAC Bounds for Learning in Exogenous Contextual MDPs
Corentin Pla, Hugo Richard, Marc Abeille +1
We study PAC learning in tabular discounted Markov decision processes with exogenous i.i.d. contexts, with discount factor , finite state space , action space $\mat…
On the Hardness of Reinforcement Learning with Transition Look-Ahead
Corentin Pla, Hugo Richard, Marc Abeille +2
We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence of actions before decidi…
Learning to Allocate Resources with Censored Feedback
Giovanni Montanari, Côme Fiegel, Corentin Pla +2
We study the online resource allocation problem in which at each round, a budget must be allocated across arms under censored feedback. An arm yields a reward if and only i…
Distribution-Aware Mean Estimation under User-level Local Differential Privacy
Corentin Pla, Hugo Richard, Maxime Vono
We consider the problem of mean estimation under user-level local differential privacy, where users are contributing through their local pool of data samples. Previous work ass…