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Multi-Armed Bandits: Theory and Applications to Online Learning in Networks

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Multi-Armed Bandits: Theory and Applications to Online Learning in Networks - Zhao, Qing, and Srikant, R (Editor)
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Multi-armed bandit problems pertain to optimal sequential decision making and learning in unknown environments. Since the first bandit problem posed by Thompson in 1933 for the application of clinical trials, bandit problems have enjoyed lasting attention from multiple research communities and have found a wide range of applications across diverse domains. This book covers classic results and recent development on both Bayesian and frequentist bandit problems. We start in Chapter 1 with a brief overview on the history of ...

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Multi-Armed Bandits: Theory and Applications to Online Learning in Networks 2019, Morgan & Claypool, San Rafael

ISBN-13: 9781627056380

Trade paperback

Multi-Armed Bandits: Theory and Applications to Online Learning in Networks 2019, Springer International Publishing AG, Cham

ISBN-13: 9783031792885

Paperback