From Regularization Operators to Support Vector Kernels
Abstract
We derive the correspondence between regularization operators used in Regularization Networks and Hilbert Schmidt Kernels appearing in Sup(cid:173) port Vector Machines. More specifica1ly, we prove that the Green's Func(cid:173) tions associated with regularization operators are suitable Support Vector Kernels with equivalent regularization properties. As a by-product we show that a large number of Radial Basis Functions namely condition(cid:173) ally positive definite functions may be used as Support Vector kernels.
Cite
Text
Smola and Schölkopf. "From Regularization Operators to Support Vector Kernels." Neural Information Processing Systems, 1997.Markdown
[Smola and Schölkopf. "From Regularization Operators to Support Vector Kernels." Neural Information Processing Systems, 1997.](https://mlanthology.org/neurips/1997/smola1997neurips-regularization/)BibTeX
@inproceedings{smola1997neurips-regularization,
title = {{From Regularization Operators to Support Vector Kernels}},
author = {Smola, Alex J. and Schölkopf, Bernhard},
booktitle = {Neural Information Processing Systems},
year = {1997},
pages = {343-349},
url = {https://mlanthology.org/neurips/1997/smola1997neurips-regularization/}
}