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Author: Johnny D. Boggs
Publisher:
ISBN:
Category : Frontier and pioneer life
Languages : en
Pages : 308
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Book Description
Author: Johnny D. Boggs
Publisher:
ISBN:
Category : Frontier and pioneer life
Languages : en
Pages : 308
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Book Description
Author: Aleksandrs Slivkins
Publisher:
ISBN: 9781680836202
Category : Computers
Languages : en
Pages : 306
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Book Description
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.
Author: Tor Lattimore
Publisher: Cambridge University Press
ISBN: 1108486827
Category : Business & Economics
Languages : en
Pages : 537
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Book Description
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Author: Johnny D. Boggs
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Johnny D. Boggs
Publisher: Penguin
ISBN: 1101220066
Category : Fiction
Languages : en
Pages : 320
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Book Description
From a Spur Award–winning author of the Five Star Western Series comes a thrilling tale of James clan. Outlaws Frank and Jesse James eluded capture for 16 years and became folk heroes. In 1882, after Jesse was killed by Bob, Frank surrendered and faced trial for murder. How could Missouri convict a man so popular that the governor almost needed an appointment to visit him in jail? William Wallace had already imprisoned one member of the untouchable James Gang. Now his case rested on the word of a scoundrel and defied those who would kill to protect Frank James. The defense would paint the Shakespeare-quoting robber as an honorable family man and victim of mistaken identity, endlessly persecuted by the hated railroads. Inside an opera house, the circus like trial would decide if James senselessly murdered a young stonemason during the 1881 Winston train robbery. Perhaps the larger question was if Missouri was ruled by the arm of the law—or the arm of the bandit.
Author: John Myles White
Publisher: "O'Reilly Media, Inc."
ISBN: 1449341586
Category : Computers
Languages : en
Pages : 88
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Book Description
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
Author: Djallel Bouneffouf
Publisher: Djallel Bouneffouf
ISBN:
Category : Computers
Languages : en
Pages : 234
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Book Description
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.
Author: Donald A. Berry
Publisher: Springer Science & Business Media
ISBN: 9401537119
Category : Science
Languages : en
Pages : 283
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Book Description
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.
Author: Yoav Freund
Publisher: Springer Science & Business Media
ISBN: 3540879862
Category : Computers
Languages : en
Pages : 480
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Book Description
This book constitutes the refereed proceedings of the 19th International Conference on Algorithmic Learning Theory, ALT 2008, held in Budapest, Hungary, in October 2008, co-located with the 11th International Conference on Discovery Science, DS 2008. The 31 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 46 submissions. The papers are dedicated to the theoretical foundations of machine learning; they address topics such as statistical learning; probability and stochastic processes; boosting and experts; active and query learning; and inductive inference.
Author: Sébastien Bubeck
Publisher: Now Pub
ISBN: 9781601986269
Category : Computers
Languages : en
Pages : 138
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Book Description
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.
