From Regularization Operators to Support Vector Kernels

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

Authors

Alex Smola, Bernhard Schölkopf

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.