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Efficient Optimal Learning for Contextual Bandits
Efficient Optimal Learning Contextual Bandits
2011/7/6
We address the problem of learning in an online setting where the learner repeatedly observes features, selects among a set of actions, and receives reward for the action taken.
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences
Finite-Time Multi-armed Bandits Problems Kullback-Leibler Divergences
2011/6/20
We consider a Kullback-Leibler-based algorithmfor the stochastic multi-armed bandit prob-
lem in the case of distributions with finite supports (not necessarily known beforehand),
whose asymptotic r...
PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
PAC-Bayesian Analysis Martingales Multiarmed Bandits
2011/6/21
We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent
random variables. The first is based on a new lemma that enables to bound expectations
of convex functions of...