EXP3 with drift detection for the switching bandit problem, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), p.2015, 2015. ,
DOI : 10.1109/DSAA.2015.7344834
Finite-time Analysis of the Multiarmed Bandit Problem, Machine Learning, vol.47, issue.2/3, pp.235-256, 2002. ,
DOI : 10.1023/A:1013689704352
The Nonstochastic Multiarmed Bandit Problem, SIAM Journal on Computing, vol.32, issue.1, pp.48-77, 2002. ,
DOI : 10.1137/S0097539701398375
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems, Foundations and Trends in Machine Learning, 2012. ,
DOI : 10.1561/2200000024
The Best of Both Worlds: Stochastic and Adversarial Bandits, Annual Conference on Learning Theory, 2012. ,
Action Elimination and Stopping Conditions for the Multi- Armed Bandit and Reinforcement Learning Problems, Journal of Machine Learning Research, vol.7, 2006. ,
Random Forest for the Contextual Bandit Problem, AISTATS, 2016. ,
On Upper- Confidence Bound Policies for Non-stationary Bandit Problems, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00281392
On Explore-Then-Commit Strategies, p.30, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01322906
Multi-armed Bandit, Dynamic Environments and Meta-Bandits, Online Trading of Exploration and Exploitation Workshop, NIPS, 2006. ,
URL : https://hal.archives-ouvertes.fr/hal-00113668
Probability Inequalities for Sums of Bounded Random Variables, Journal of the American Statistical Association, vol.1, issue.301, pp.13-30, 1963. ,
DOI : 10.1007/BF02883985
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models, Journal of Machine Learning Research, vol.17, issue.1, pp.1-42, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01024894
Explore no more: improved highprobability regret bounds for non-stochastic bandits, NIPS, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01223501
One Practical Algorithm for Both Stochastic and Adversarial Bandits, 31th Intl. Conf. on Machine Learning (ICML), 2014. ,
Probability Inequalities for the Sum in Sampling without Replacement. Pages 39?48 of: The Annals of Statistics, 1974. ,
ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES, Biometrika, vol.25, issue.3-4, pp.285-294, 1933. ,
DOI : 10.1093/biomet/25.3-4.285
Piecewisestationary Bandit Problems with Side Observations, 2009. ,