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.

Author: Felipe Cucker, Ding Xuan Zhou
Binding Type: Hardcover
Publisher: Cambridge University Press
Published: 05/14/2007
Series: Cambridge Monographs on Applied and Computational Mathematics (Hardcover) #24
Pages: 238
Weight: 0.79lbs
Size: 9.08h x 6.30w x 0.66d
ISBN: 9780521865593

About the Author
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.