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Statistical learning theory

Author: Vladimir Naumovich Vapnik
Publisher: New York : Wiley, ©1998.
Series: Adaptive and learning systems for signal processing, communications, and control.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:

This book is devoted to the statistical theory of learning and generalization, that is, the problem of choosing the desired function on the basis of empirical data. The author will present the whole  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Vapnik, Vladimir Naumovich.
Statistical learning theory.
New York : Wiley, ©1998
(DLC) 97037075
(OCoLC)37567297
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Vladimir Naumovich Vapnik
ISBN: 0585357056 9780585357058
OCLC Number: 47011219
Notes: "A Wiley-Interscience publication."
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2011. MiAaHDL
Description: 1 online resource (xxiv, 736 pages) : illustrations.
Details: 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.
Contents: Partial table of contents: THEORY OF LEARNING AND GENERALIZATION. Two Approaches to the Learning Problem. Estimation of the Probability Measure and Problem of Learning. Conditions for Consistency of Empirical Risk Minimization Principle. The Structural Risk Minimization Principle. Stochastic Ill-Posed Problems. SUPPORT VECTOR ESTIMATION OF FUNCTIONS. Perceptrons and Their Generalizations. SV Machines for Function Approximations, Regression Estimation, and Signal Processing. STATISTICAL FOUNDATION OF LEARNING THEORY. Necessary and Sufficient Conditions for Uniform Convergence of Frequencies to Their Probabilities. Necessary and Sufficient Conditions for Uniform One-Sided Convergence of Means to Their Expectations. Comments and Bibliographical Remarks. References. Index.
Series Title: Adaptive and learning systems for signal processing, communications, and control.
Responsibility: Vladimir N. Vapnik.

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