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The combinatorial stochastic semi-bandit problem is an extension of the classical multi-armed bandit problem in which an algorithm pulls more than one arm at each stage and the rewards of all pulled arms are revealed.
Asymptotically efficient adaptive allocation rules
Tze Leung Lai and Herbert Robbins · 1985
Earlier work this paper cites.
Some aspects of the sequential design of experiments
Herbert Robbins · 1985
Earlier work this paper cites.
Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer · 2002
Earlier work this paper cites.
Self-normalized processes: Limit theory and Statistical Applications
Victor H Peña, Tze Leung Lai, and Qi-Man Shao · 2008
Earlier work this paper cites.
Parametric Bandits: The Generalized Linear Case
Sarah Filippi, Olivier Cappé, Aurélien Garivier, and Csaba Szepesvári · 2010
Earlier work this paper cites.
Linearly Parameterized Bandits
Paat Rusmevichientong and John N. Tsitsiklis · 2010
Earlier work this paper cites.
Improved Algorithms for Linear Stochastic Bandits
Yasin Abbasi-Yadkori, David Pal, and Csaba Szepesvari · 2011
Cited alongside, same era.
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit
Alexandra Carpentier and Rémi Munos · 2012
Cited alongside, same era.
Combinatorial bandits
Nicolo Cesa-Bianchi and Gábor Lugosi · 2012
Cited alongside, same era.
Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations
Yi Gai, Bhaskar Krishnamachari, and Rahul Jain · 2012
Cited alongside, same era.
Regret in online combinatorial optimization
Jean-Yves Audibert, Sébastien Bubeck, and Gábor Lugosi · 2013
Cited alongside, same era.
Combinatorial multi-armed bandit: General framework and applications
Wei Chen, Yajun Wang, and Yang Yuan · 2013
Later among the works it cites.
Informational confidence bounds for self-normalized averages and applications
Aurélien Garivier · 2013
Later among the works it cites.
Combinatorial Bandits Revisited
Richard Combes, M. Sadegh Talebi, Alexandre Proutiere, and Marc Lelarge · 2015
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Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays
Junpei Komiyama, Junya Honda, and Hiroshi Nakagawa · 2015
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Tight regret bounds for stochastic combinatorial semi-bandits
Branislav Kveton, Zheng Wen, Azin Ashkan, and Csaba Szepesvari · 2015
Later among the works it cites.
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