Frame, Reproducing Kernel, Regularization and Learning (2005)
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by
Alain Rakotomamonjy
,
Stéphane Canu
| Venue: | JOURNAL OF MACHINE LEARNING RESEARCH |
BibTeX
@MISC{Rakotomamonjy05frame,reproducing,
author = {Alain Rakotomamonjy and Stéphane Canu},
title = {Frame, Reproducing Kernel, Regularization and Learning},
year = {2005}
}
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Abstract
This work deals with a method for building Reproducing Kernel Hilbert Space (RKHS) from a Hilbert space with frame elements having special properties. Conditions on existence and a method of construction are given. Then, these RKHS are used within the framework of regularization theory for function approximation. Implications on semiparametric estimation are discussed and a multiscale scheme of regularization is also proposed. Results on toy and real-world approximation problems illustrate the effectiveness of such methods.
