688 citations · 2k across the 44 of their papers we have counts for
17 papers · 1 filter
A Non-asymptotic Approach to Best-Arm Identification for Gaussian Bandits
Antoine Barrier, Aurélien Garivier, Tomáš Kocák
We propose a new strategy for best-arm identification with fixed confidence of Gaussian variables with bounded means and unit variance. This strategy, called Exploration-Biased Sam…
Thresholding Bandit for Dose-ranging: The Impact of Monotonicity
Aurélien Garivier, Pierre Ménard, Laurent Rossi +1
We analyze the sample complexity of the thresholding bandit problem, with and without the assumption that the mean values of the arms are increasing. In each case, we provide a low…
On Explore-Then-Commit Strategies
Aurélien Garivier, Emilie Kaufmann, Tor Lattimore
We study the problem of minimising regret in two-armed bandit problems with Gaussian rewards. Our objective is to use this simple setting to illustrate that strategies based on an…
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…
Explore First, Exploit Next: The True Shape of Regret in Bandit Problems
Aurélien Garivier, Pierre Ménard, Gilles Stoltz
We revisit lower bounds on the regret in the case of multi-armed bandit problems. We obtain non-asymptotic, distribution-dependent bounds and provide straightforward proofs based o…
Optimal Best Arm Identification with Fixed Confidence
Aurélien Garivier, Emilie Kaufmann
We give a complete characterization of the complexity of best-arm identification in one-parameter bandit problems. We prove a new, tight lower bound on the sample complexity. We pr…