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We investigate the piecewise-stationary combinatorial semi-bandit problem.
On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
William R Thompson · 1933
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Asymptotically efficient adaptive allocation rules
Tze Leung Lai and Herbert Robbins · 1985
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Detection of abrupt changes: theory and application , volume 104
Michèle Basseville and Igor V Nikiforov · 1993
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Approximate solution of NP optimization problems
Giorgio Ausiello, Pierluigi Crescenzi, and Marco Protasi · 1995
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Discounted UCB
Levente Kocsis and Csaba Szepesvári · 2006
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Change point detection and meta-bandits for online learning in dynamic environments
Cédric Hartland, Nicolas Baskiotis, Sylvain Gelly, Michèle Sebag, and Olivier Teytaud · 2007
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Piecewise-stationary bandit problems with side observations
Jia Yuan Yu and Shie Mannor · 2009
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On upper-confidence bound policies for switching bandit problems
Aurélien Garivier and Eric Moulines · 2011
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Better algorithms for benign bandits
Elad Hazan and Satyen Kale · 2011
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Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms
Lihong Li, Wei Chu, John Langford, and Xuanhui Wang · 2011
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Analysis of Thompson sampling for the multi-armed bandit problem
Shipra Agrawal and Navin Goyal · 2012
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Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Sébastien Bubeck and Nicolo Cesa-Bianchi · 2012
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Kullback–leibler upper confidence bounds for optimal sequential allocation
Olivier Cappé, Aurélien Garivier, Odalric-Ambrym Maillard, Rémi Munos, Gilles Stoltz, et al · 2013
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Combinatorial multi-armed bandit: General framework and applications
Wei Chen, Yajun Wang, and Yang Yuan · 2013
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Thompson sampling in switching environments with bayesian online change detection
Joseph Mellor and Jonathan Shapiro · 2013
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Sequential analysis: tests and confidence intervals
David Siegmund · 2013
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Automatic ad format selection via contextual bandits
Liang Tang, Romer Rosales, Ajit Singh, and Deepak Agarwal · 2013
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Stochastic multi-armed-bandit problem with non-stationary rewards
Omar Besbes, Yonatan Gur, and Assaf Zeevi · 2014
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A multi-armed bandit approach to online spatial task assignment
Umair Ul Hassan and Edward Curry · 2014
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Mixture martingales revisited with applications to sequential tests and confidence intervals
Emilie Kaufmann and Wouter Koolen · 2018
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Tor Lattimore and Csaba Szepesvári · 2018
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A change-detection based framework for piecewise-stationary multi-armed bandit problem
Fang Liu, Joohyun Lee, and Ness Shroff · 2018
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On analyzing user preference dynamics with temporal social networks
Fabíola SF Pereira, João Gama, Sandra de Amo, and Gina MB Oliveira · 2018
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Thompson sampling for combinatorial semi-bandits
Siwei Wang and Wei Chen · 2018
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On abruptly-changing and slowly-varying multiarmed bandit problems
Lai Wei and Vaibhav Srivatsva · 2018
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Reliable crowdsourcing for multi-class labeling using coding theory
Aditya Vempaty, Lav R Varshney, and Pramod K Varshney · 2014
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On top-k selection in multi-armed bandits and hidden bipartite graphs
Wei Cao, Jian Li, Yufei Tao, and Zhize Li · 2015
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Introduction to online convex optimization
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Collaborative filtering bandits
Shuai Li, Alexandros Karatzoglou, and Claudio Gentile · 2016
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Adaptively tracking the best bandit arm with an unknown number of distribution changes
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