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.
| ISBN: | 9783034894302 |
| Publication date: | 1st November 2012 |
| Author: | Daniel Alpay |
| Publisher: | Birkhauser an imprint of Birkhäuser Basel |
| Format: | Paperback |
| Pagination: | 344 pages |
| Series: | Operator Theory: Advances and Applications |
| Genres: |
Functional analysis and transforms Differential calculus and equations Integral calculus and equations Complex analysis, complex variables |
20. Pattern recognition and statistical learning theory (the theory of support vector machines).
Reproducing Kernel Spaces and Applications features in the following genres: Functional analysis and transforms, Differential calculus and equations, Integral calculus and equations, Complex analysis, complex variables
Paperback, Hardback. Not Available.
Reproducing Kernel Spaces and Applications was written by Daniel Alpay and published by Birkhauser an imprint of Birkhäuser Basel
Reproducing Kernel Spaces and Applications has 344 pages
Yes it is part of Operator Theory: Advances and Applications series