  This paper is devoted to the study of the max K-armed bandit problem, which
consists in sequentially allocating resources in order to detect extreme
values. Our contribution is twofold. We first significantly refine the analysis
of the ExtremeHunter algorithm carried out in Carpentier and Valko (2014), and
next propose an alternative approach, showing that, remarkably, Extreme Bandits
can be reduced to a classical version of the bandit problem to a certain
extent. Beyond the formal analysis, these two approaches are compared through
numerical experiments.
