
Learning Theory - Hardcover
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Availability:In StockContributor:Felipe Cucker, Ding Xuan ZhouSeries:Cambridge Monographs on Applied and Computational Mathematics (Hardcover)Publish date:2007-05-14Pages:238
Languages:EnglishPublisher:Cambridge University PressISBN-13:9780521865593ISBN-10:052186559XUPC:9780521865593Book Category:ComputersBook Subcategory:Artificial IntelligenceBook Topic:Computer Vision & Pattern RecognitionSize:9.08 x 6.30 x 0.66 inchesWeight:0.79Product ID:SC0TD6RRF4
The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines.
Languages:EnglishPublisher:Cambridge University PressISBN-13:9780521865593ISBN-10:052186559XUPC:9780521865593Book Category:ComputersBook Subcategory:Artificial IntelligenceBook Topic:Computer Vision & Pattern RecognitionSize:9.08 x 6.30 x 0.66 inchesWeight:0.79Product ID:SC0TD6RRF4
Cucker, Felipe: - Felipe Cucker is a Professor of Mathematics at the City University of Hong Kong.Zhou, Ding Xuan: - Ding Xuan Zhou is an Associate Professor in the Department of Mathematics at the City University of Hong Kong.
Publisher: Cambridge University Press
Contributor(s)
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