Learning Theory - An Approximation Theory Viewpoint (Hardcover)

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.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Series:	Cambridge Monographs on Applied and Computational Mathematics
Release date:	March 2007
First published:	2007
Authors:	Felipe Cucker • Ding-Xuan Zhou
Dimensions:	231 x 160 x 17mm (L x W x T)
Format:	Hardcover
Pages:	238
ISBN-13:	978-0-521-86559-3
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Promotions
LSN:	0-521-86559-X
Barcode:	9780521865593

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