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E-book
Author NATO Advanced Study Institute on Learning Theory and Practice (2002 : Louvain, Belgium)

Title Advances in learning theory : methods, models and applications / edited by Johan Suykens [and others]
Published Amsterdam ; Washington, DC : IOS Press ; Tokyo : Ohmsha, ©2003

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Description 1 online resource (xxi, 415 pages) : illustrations
Series NATO science series. Series III, Computer and systems sciences, 1387-6694 ; v. 190
NATO science series. Series III, Computer and systems sciences ; v. 190. 1387-6694
Contents Cover; Title page; Preface; Organizing committee; List of chapter contributors; Contents; 1 An Overview of Statistical Learning Theory; 2 Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem; 3 Cucker Smale Learning Theory in Besov Spaces; 4 High-dimensional Approximation by Neural Networks; 5 Functional Learning through Kernels; 6 Leave-one-out Error and Stability of Learning Algorithms with Applications; 7 Regularized Least-Squares Classification; 8 Support Vector Machines: Least Squares Approaches and Extensions
Summary This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics
Notes "Proceedings of the NATO Advanced Study Institute on Learning Theory and Practice, 8-19 July 2002, Leuven, Belgium"--Title page verso
"Published in cooperation with NATO Scientific Affairs Division."
Bibliography Includes bibliographical references and indexes
Notes Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL
Print version record
digitized 2011 HathiTrust Digital Library committed to preserve pda MiAaHDL
Subject Computational learning theory -- Congresses
Machine learning -- Mathematical models -- Congresses
COMPUTERS -- Enterprise Applications -- Business Intelligence Tools.
COMPUTERS -- Intelligence (AI) & Semantics.
Computational learning theory
Machine learning -- Mathematical models
Genre/Form Conference papers and proceedings
Form Electronic book
Author Suykens, Johan A. K
ISBN 1586033417
9781586033415
427490587X
9784274905872
1417511397
9781417511396
1601294018
9781601294012