William Réveillard — accepted AI-conference papers

2025

Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms

NeurIPS 2025poster

We consider a stochastic multi-armed bandit problem with i.i.d. rewards where the expected reward function is multimodal with at most $m$ modes. We propose the first known computationally tractable algorithm for computing the solution to the Graves-Lai optimization problem, which in turn enables the…

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2024

Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery

Yassir Jedra, William Réveillard, Stefan Stojanovic, Alexandre Proutiere

ICML 2024poster

We study contextual bandits with low-rank structure where, in each round, if the (context, arm) pair $(i,j)\in [m]\times [n]$ is selected, the learner observes a noisy sample of the $(i,j)$-th entry of an unknown low-rank reward matrix. Successive contexts are generated randomly in an i.i.d. manner…

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