Overview
- Special selection of invited original papers collected from a leading expert in the field
- Of importance for many fields inside and outside mathematics
Part of the book series: Operator Theory: Advances and Applications (OT, volume 143)
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20. Pattern recognition and statistical learning theory (the theory of support vector machines). See [40], [58]. In this last volume we refer in particular to the papers [63] and [64]. Since this topic is maybe less known to the operator theory community we mention that the support vector method is a general approach to function estimation problems. See [63, p. 26]. We note that the above list and the given references are by no way exhaustive. We refer to the first section of the paper of S. Saitoh in the present volume for another (and mainly different) list of topics where reproducing kernel spaces appear. Quite often a given question is best understood in a reproducing kernel Hilbert space (for instance when using Cauchy's formula in the Hardy space H ) 2 and one finds oneself as Mr Jourdain of Moliere' Bourgeois Gentilhomme speaking Prose without knowing it [48, p. 51]: Par ma foil il y a plus de quarante ans que je dis de la prose sans que l j'en susse rien.
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Table of contents (12 chapters)
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Front Matter
Editors and Affiliations
Bibliographic Information
Book Title: Reproducing Kernel Spaces and Applications
Editors: Daniel Alpay
Series Title: Operator Theory: Advances and Applications
DOI: https://doi.org/10.1007/978-3-0348-8077-0
Publisher: Birkhäuser Basel
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eBook Packages: Springer Book Archive
Copyright Information: Springer Basel AG 2003
Hardcover ISBN: 978-3-7643-0068-5Published: 29 August 2003
Softcover ISBN: 978-3-0348-9430-2Published: 01 November 2012
eBook ISBN: 978-3-0348-8077-0Published: 06 December 2012
Series ISSN: 0255-0156
Series E-ISSN: 2296-4878
Edition Number: 1
Number of Pages: XV, 344
Topics: Operator Theory, Functional Analysis, Functions of a Complex Variable, Integral Transforms, Operational Calculus, Partial Differential Equations