1 citations · 1 across the 3 of their papers we have counts for
3 papers
Privacy Amplification via Shuffling for Linear Contextual Bandits
Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet +1
Contextual bandit algorithms are widely used in domains where it is desirable to provide a personalized service by leveraging contextual information, that may contain sensitive inf…
Differentially Private Exploration in Reinforcement Learning with Linear Representation
Paul Luyo, Evrard Garcelon, Alessandro Lazaric +1
This paper studies privacy-preserving exploration in Markov Decision Processes (MDPs) with linear representation. We first consider the setting of linear-mixture MDPs (Ayoub et al.…
Top Ranking for Multi-Armed Bandit with Noisy Evaluations
Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric +1
We consider a multi-armed bandit setting where, at the beginning of each round, the learner receives noisy independent, and possibly biased, \emph{evaluations} of the true reward o…