most citedRegret lower bounds and extended Upper Confidence Bounds policies in stochastic multi-armed bandit problem

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stat.ML2011★ 3 cited

Regret lower bounds and extended Upper Confidence Bounds policies in stochastic multi-armed bandit problem

Antoine Salomon, Jean-Yves Audibert, Issam El Alaoui

This paper is devoted to regret lower bounds in the classical model of stochastic multi-armed bandit. A well-known result of Lai and Robbins, which has then been extended by Burnet…

stat.ML2011

Robustness of Anytime Bandit Policies

Antoine Salomon, Jean-Yves Audibert

This paper studies the deviations of the regret in a stochastic multi-armed bandit problem. When the total number of plays n is known beforehand by the agent, Audibert et al. (2009…