Prediction, Learning, and Games

By: Nicolo Cesa-Bianchi, Gabor Lugosi

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Hardcover | 13 March 2006

At a Glance

Hardcover
408 Pages

Dimensions(cm)
25.4 x 17.78 x 2.54

Hardcover

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This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first 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. Old and new forecasting methods are described in a mathematically precise way in order to characterize their theoretical limitations and possibilities.

Industry Reviews

"Each chapter contains about two dozen inspiring problems, and the book refers to more than 300 up-to-date sources... The book is addressed to graduate students and researchers in the fields of engineering and information, computer sciences, and data analysis; it presents both theoretical inference and practical hands-on usage of modern prediction techniques." Stan Lipovektsy, GfK Custom Research North America Technometrics, May 2007

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You Can Find This Book In

Non-Fiction Mathematics Optimisation Game Theory Probability & Statistics Computing & I.T.Digital Lifestyle & Online World: Consumer & User Guides Computer Games & Online Games Strategy Guides Computer Science Artificial Intelligence Computer Vision Pattern Recognition

Introduction
Prediction with expert advice
Tight bounds for specific losses
Randomized prediction
Efficient forecasters for large classes of experts
Prediction with limited feedback
Prediction and playing games
Absolute loss
Logarithmic loss
Sequential investment
Linear pattern recognition
Linear classification
Appendix.
Table of Contents provided by Publisher. All Rights Reserved.

Prediction, Learning, and Games

At a Glance

Hardcover

Industry Reviews

Shipping

How to return your order

Defective items

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