Introduction to Multi-Armed Bandits

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Publisher :
ISBN 13 : 9781680836202
Total Pages : 306 pages
Book Rating : 4.0X/5 ( download)

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Book Synopsis Introduction to Multi-Armed Bandits by : Aleksandrs Slivkins

Download or read book Introduction to Multi-Armed Bandits written by Aleksandrs Slivkins and published by . This book was released on 2019-10-31 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first book to provide a textbook like treatment of the subject.

Multi-armed Bandit Problem and Application

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Publisher : Djallel Bouneffouf
ISBN 13 :
Total Pages : 234 pages
Book Rating : 4./5 ( download)

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Book Synopsis Multi-armed Bandit Problem and Application by : Djallel Bouneffouf

Download or read book Multi-armed Bandit Problem and Application written by Djallel Bouneffouf and published by Djallel Bouneffouf. This book was released on 2023-03-14 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the multi-armed bandit (MAB) framework has attracted a lot of attention in various applications, from recommender systems and information retrieval to healthcare and finance. This success is due to its stellar performance combined with attractive properties, such as learning from less feedback. The multiarmed bandit field is currently experiencing a renaissance, as novel problem settings and algorithms motivated by various practical applications are being introduced, building on top of the classical bandit problem. This book aims to provide a comprehensive review of top recent developments in multiple real-life applications of the multi-armed bandit. Specifically, we introduce a taxonomy of common MAB-based applications and summarize the state-of-the-art for each of those domains. Furthermore, we identify important current trends and provide new perspectives pertaining to the future of this burgeoning field.

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems

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Publisher : Now Pub
ISBN 13 : 9781601986269
Total Pages : 138 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems by : Sébastien Bubeck

Download or read book Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems written by Sébastien Bubeck and published by Now Pub. This book was released on 2012 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph, the focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed payoffs and adversarial payoffs. Besides the basic setting of finitely many actions, it analyzes some of the most important variants and extensions, such as the contextual bandit model.

Multi-armed Bandit Allocation Indices

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Publisher : John Wiley & Sons
ISBN 13 : 1119990211
Total Pages : 233 pages
Book Rating : 4.15/5 ( download)

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Book Synopsis Multi-armed Bandit Allocation Indices by : John Gittins

Download or read book Multi-armed Bandit Allocation Indices written by John Gittins and published by John Wiley & Sons. This book was released on 2011-02-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems. Since then there has been a remarkable flowering of new insights, generalizations and applications, to which Glazebrook and Weber have made major contributions. This second edition brings the story up to date. There are new chapters on the achievable region approach to stochastic optimization problems, the construction of performance bounds for suboptimal policies, Whittle's restless bandits, and the use of Lagrangian relaxation in the construction and evaluation of index policies. Some of the many varied proofs of the index theorem are discussed along with the insights that they provide. Many contemporary applications are surveyed, and over 150 new references are included. Over the past 40 years the Gittins index has helped theoreticians and practitioners to address a huge variety of problems within chemometrics, economics, engineering, numerical analysis, operational research, probability, statistics and website design. This new edition will be an important resource for others wishing to use this approach.

Multi-armed Bandits

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Publisher : Synthesis Lectures on Communic
ISBN 13 : 9781681736372
Total Pages : 147 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Multi-armed Bandits by : Qing Zhao

Download or read book Multi-armed Bandits written by Qing Zhao and published by Synthesis Lectures on Communic. This book was released on 2019-11-21 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 bandit problems, contrasting the two schools-Bayesian and frequentis -of approaches and highlighting foundational results and key applications. Chapters 2 and 4 cover, respectively, the canonical Bayesian and frequentist bandit models. In Chapters 3 and 5, we discuss major variants of the canonical bandit models that lead to new directions, bring in new techniques, and broaden the applications of this classical problem. In Chapter 6, we present several representative application examples in communication networks and social-economic systems, aiming to illuminate the connections between the Bayesian and the frequentist formulations of bandit problems and how structural results pertaining to one may be leveraged to obtain solutions under the other.

Bandit Algorithms

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Publisher : Cambridge University Press
ISBN 13 : 1108486827
Total Pages : 537 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis Bandit Algorithms by : Tor Lattimore

Download or read book Bandit Algorithms written by Tor Lattimore and published by Cambridge University Press. This book was released on 2020-07-16 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.

Bandit problems

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Publisher : Springer Science & Business Media
ISBN 13 : 9401537119
Total Pages : 283 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Bandit problems by : Donald A. Berry

Download or read book Bandit problems written by Donald A. Berry and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our purpose in writing this monograph is to give a comprehensive treatment of the subject. We define bandit problems and give the necessary foundations in Chapter 2. Many of the important results that have appeared in the literature are presented in later chapters; these are interspersed with new results. We give proofs unless they are very easy or the result is not used in the sequel. We have simplified a number of arguments so many of the proofs given tend to be conceptual rather than calculational. All results given have been incorporated into our style and notation. The exposition is aimed at a variety of types of readers. Bandit problems and the associated mathematical and technical issues are developed from first principles. Since we have tried to be comprehens ive the mathematical level is sometimes advanced; for example, we use measure-theoretic notions freely in Chapter 2. But the mathema tically uninitiated reader can easily sidestep such discussion when it occurs in Chapter 2 and elsewhere. We have tried to appeal to graduate students and professionals in engineering, biometry, econ omics, management science, and operations research, as well as those in mathematics and statistics. The monograph could serve as a reference for professionals or as a telA in a semester or year-long graduate level course.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 364204414X
Total Pages : 410 pages
Book Rating : 4.44/5 ( download)

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Book Synopsis Algorithmic Learning Theory by : Ricard Gavaldà

Download or read book Algorithmic Learning Theory written by Ricard Gavaldà and published by Springer. This book was released on 2009-09-29 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th International Conference on Algorithmic Learning Theory, ALT 2009, held in Porto, Portugal, in October 2009, co-located with the 12th International Conference on Discovery Science, DS 2009. The 26 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 60 submissions. The papers are divided into topical sections of papers on online learning, learning graphs, active learning and query learning, statistical learning, inductive inference, and semisupervised and unsupervised learning. The volume also contains abstracts of the invited talks: Sanjoy Dasgupta, The Two Faces of Active Learning; Hector Geffner, Inference and Learning in Planning; Jiawei Han, Mining Heterogeneous; Information Networks By Exploring the Power of Links, Yishay Mansour, Learning and Domain Adaptation; Fernando C.N. Pereira, Learning on the Web.

Foundations and Applications of Sensor Management

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Publisher : Springer Science & Business Media
ISBN 13 : 0387498192
Total Pages : 317 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Foundations and Applications of Sensor Management by : Alfred Olivier Hero

Download or read book Foundations and Applications of Sensor Management written by Alfred Olivier Hero and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers control theory signal processing and relevant applications in a unified manner. It introduces the area, takes stock of advances, and describes open problems and challenges in order to advance the field. The editors and contributors to this book are pioneers in the area of active sensing and sensor management, and represent the diverse communities that are targeted.

Bandit Algorithms for Website Optimization

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449341586
Total Pages : 88 pages
Book Rating : 4.89/5 ( download)

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Book Synopsis Bandit Algorithms for Website Optimization by : John Myles White

Download or read book Bandit Algorithms for Website Optimization written by John Myles White and published by "O'Reilly Media, Inc.". This book was released on 2012-12-10 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: When looking for ways to improve your website, how do you decide which changes to make? And which changes to keep? This concise book shows you how to use Multiarmed Bandit algorithms to measure the real-world value of any modifications you make to your site. Author John Myles White shows you how this powerful class of algorithms can help you boost website traffic, convert visitors to customers, and increase many other measures of success. This is the first developer-focused book on bandit algorithms, which were previously described only in research papers. You’ll quickly learn the benefits of several simple algorithms—including the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithms—by working through code examples written in Python, which you can easily adapt for deployment on your own website. Learn the basics of A/B testing—and recognize when it’s better to use bandit algorithms Develop a unit testing framework for debugging bandit algorithms Get additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials