@inproceedings{75e19fa857ed4135849bdb3dd517c8ee,
title = "Anytime optimal algorithms in stochastic multi-armed bandits",
abstract = "We introduce an anytime algorithm for stochastic multi-armed bandit with optimal distribution free and distribution dependent bounds (for a specific family of parameters). The performances of this algorithm (as well as another one motivated by the conjectured optimal bound) are evaluated empirically. A similar analysis is provided with full information, to serve as a benchmark.",
author = "R{\'e}my Degenne and Vianney Perchet",
note = "Publisher Copyright: {\textcopyright} 2016 by the author(s).; 33rd International Conference on Machine Learning, ICML 2016 ; Conference date: 19-06-2016 Through 24-06-2016",
year = "2016",
month = jan,
day = "1",
language = "English",
series = "33rd International Conference on Machine Learning, ICML 2016",
publisher = "International Machine Learning Society (IMLS)",
pages = "2391--2409",
editor = "Weinberger, \{Kilian Q.\} and Balcan, \{Maria Florina\}",
booktitle = "33rd International Conference on Machine Learning, ICML 2016",
}