19 citations · 30 across the 2 of their papers we have counts for
3 papers
cs.LG2017★ 19 cited
Corrupt Bandits for Preserving Local Privacy
Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann
We study a variant of the stochastic multi-armed bandit (MAB) problem in which the rewards are corrupted. In this framework, motivated by privacy preservation in online recommender…
stat.ML2017★ 11 cited
Monte-Carlo Tree Search by Best Arm Identification
Emilie Kaufmann, Wouter Koolen
Recent advances in bandit tools and techniques for sequential learning are steadily enabling new applications and are promising the resolution of a range of challenging related pro…
math.ST2016
Maximin Action Identification: A New Bandit Framework for Games
Aurélien Garivier, Emilie Kaufmann, Wouter Koolen
We study an original problem of pure exploration in a strategic bandit model motivated by Monte Carlo Tree Search. It consists in identifying the best action in a game, when the pl…