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About this product
- DescriptionThe 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.
- Author BiographyFelipe Cucker is a Professor of Mathematics at the City University of Hong Kong. Ding Xuan Zhou is an Associate Professor in the Department of Mathematics at the City University of Hong Kong.
- Author(s)Ding Xuan Zhou,Felipe Cucker
- PublisherCambridge University Press
- Date of Publication29/03/2007
- SubjectComputing: General
- Series TitleCambridge Monographs on Applied and Computational Mathematics
- Series Part/Volume NumberNo. 24
- Place of PublicationCambridge
- Country of PublicationUnited Kingdom
- ImprintCambridge University Press
- Content Note20 b/w illus.
- Weight520 g
- Width152 mm
- Height228 mm
- Spine17 mm
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