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Learning theory : an approximation theory viewpoint

Author: Felipe Cucker; Ding-Xuan Zhou
Publisher: Cambridge, UK ; New York : Cambridge University Press, 2007.
Series: Cambridge monographs on applied and computational mathematics.
Edition/Format:   Print book : Document   Computer File : EnglishView all editions and formats
Database:WorldCat
Summary:
The goal of learning theory is to approximate a function from sample values. To attain this goal it draws on statistics, approximation theory and algorithmics. This book aims to give a general overview of the theoretical foundations of learnign theory.
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Material Type: Document, Internet resource
Document Type: Book, Computer File, Internet Resource
All Authors / Contributors: Felipe Cucker; Ding-Xuan Zhou
ISBN: 9780521865593 052186559X 0511273282 9780511273285 0511274076 9780511274077
OCLC Number: 76141644
Description: xii, 224 pages : illustrations ; 24 cm.
Contents: The framework of learning --
Basic hypothesis spaces --
Estimating the sample error --
Polynomial decay of the approximation error --
Estimating covering numbers --
Logarithmic decay of the approximation error --
On the bias-variance problem --
Least squares regularization --
Support vector machines for classification --
General regularized classifiers.
Series Title: Cambridge monographs on applied and computational mathematics.
Responsibility: Felipe Cucker, Ding-Xuan Zhou.
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A general overview of theoretical foundations; the first book to emphasize the approximation theory viewpoint.  Read more...

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'The book is well suited for its target audience, which includes researchers and graduate students. They will, no doubt, be reassured to find that each chapter closes with a collection of references Read more...

 
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