Regret Analysis Of Stochastic And Nonstochastic Multi Armed Bandit Problems
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Regret Analysis Of Stochastic And Nonstochastic Multi Armed Bandit Problems
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Author : Sébastien Bubeck
language : en
Publisher:
Release Date : 2012
Regret Analysis Of Stochastic And Nonstochastic Multi Armed Bandit Problems written by Sébastien Bubeck and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Artificial intelligence categories.
Multi-armed bandit problems are the most basic examples of sequential decision problems with an exploration-exploitation trade-off. This is the balance between staying with the option that gave highest payoffs in the past and exploring new options that might give higher payoffs in the future. 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 also analyzes some of the most important variants and extensions, such as the contextual bandit model.
Regret Analysis Of Stochastic And Nonstochastic Multi Armed Bandit Problems
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Author : Sébastien Bubeck
language : en
Publisher: Now Pub
Release Date : 2012
Regret Analysis Of Stochastic And Nonstochastic Multi Armed Bandit Problems written by Sébastien Bubeck and has been published by Now Pub this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
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.
Introduction To Multi Armed Bandits
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Author : Aleksandrs Slivkins
language : en
Publisher:
Release Date : 2019-10-31
Introduction To Multi Armed Bandits written by Aleksandrs Slivkins and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.
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.
Algorithmic Learning Theory
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Author : Ricard Gavaldà
language : en
Publisher: Springer
Release Date : 2009-09-29
Algorithmic Learning Theory written by Ricard Gavaldà and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-29 with Computers categories.
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.
Bandit Algorithms
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Author : Tor Lattimore
language : en
Publisher: Cambridge University Press
Release Date : 2020-07-16
Bandit Algorithms written by Tor Lattimore and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-16 with Business & Economics categories.
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Prediction Learning And Games
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Author : Nicolo Cesa-Bianchi
language : en
Publisher: Cambridge University Press
Release Date : 2006-03-13
Prediction Learning And Games written by Nicolo Cesa-Bianchi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-13 with Computers categories.
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Convex Optimization
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Author : Sébastien Bubeck
language : en
Publisher: Foundations and Trends (R) in Machine Learning
Release Date : 2015-11-12
Convex Optimization written by Sébastien Bubeck and has been published by Foundations and Trends (R) in Machine Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-12 with Convex domains categories.
This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-box optimization and proceeds to guide the reader through recent advances in structural optimization and stochastic optimization. The presentation of black-box optimization, strongly influenced by the seminal book by Nesterov, includes the analysis of cutting plane methods, as well as (accelerated) gradient descent schemes. Special attention is also given to non-Euclidean settings (relevant algorithms include Frank-Wolfe, mirror descent, and dual averaging), and discussing their relevance in machine learning. The text provides a gentle introduction to structural optimization with FISTA (to optimize a sum of a smooth and a simple non-smooth term), saddle-point mirror prox (Nemirovski's alternative to Nesterov's smoothing), and a concise description of interior point methods. In stochastic optimization it discusses stochastic gradient descent, mini-batches, random coordinate descent, and sublinear algorithms. It also briefly touches upon convex relaxation of combinatorial problems and the use of randomness to round solutions, as well as random walks based methods.
Bandit Problems
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Author : Donald A. Berry
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Bandit Problems written by Donald A. Berry and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Science categories.
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.
Computational Collective Intelligence
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2020-11-23
Computational Collective Intelligence written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Computers categories.
This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; applications of collective intelligence; data mining methods and applications; machine learning methods; deep learning and applications for industry 4.0; computer vision techniques; biosensors and biometric techniques; innovations in intelligent systems; natural language processing; low resource languages processing; computational collective intelligence and natural language processing; computational intelligence for multimedia understanding; and intelligent processing of multimedia in web systems. *The conference was held virtually due to the COVID-19 pandemic.
Uncontrolled
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Author : Jim Manzi
language : en
Publisher: Basic Books
Release Date : 2012-05-01
Uncontrolled written by Jim Manzi and has been published by Basic Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-01 with Political Science categories.
How do we know which social and economic policies work, which should be continued, and which should be changed? Jim Manzi argues that throughout history, various methods have been attempted -- except for controlled experimentation. Experiments provide the feedback loop that allows us, in certain limited ways, to identify error in our beliefs as a first step to correcting them. Over the course of the first half of the twentieth century, scientists invented a methodology for executing controlled experiments to evaluate certain kinds of proposed social interventions. This technique goes by many names in different contexts (randomized control trials, randomized field experiments, clinical trials, etc.). Over the past ten to twenty years this has been increasingly deployed in a wide variety of contexts, but it remains the red-haired step child of modern social science. This is starting to change, and this change should be encouraged and accelerated, even though the staggering complexity of human society creates severe limits to what social science could be realistically expected to achieve. Randomized trials have shown, for example, that work requirements for welfare recipients have succeeded like nothing else in encouraging employment, that charter school vouchers have been successful in increasing educational attainment for underprivileged children, and that community policing has worked to reduce crime, but also that programs like Head Start and Job Corps, which might be politically attractive, fail to attain their intended objectives. Business leaders can also use experiments to test decisions in a controlled, low-risk environment before investing precious resources in large-scale changes -- the philosophy behind Manzi's own successful software company. In a powerful and masterfully-argued book, Manzi shows us how the methods of science can be applied to social and economic policy in order to ensure progress and prosperity.