Open AccessProceedings Article
From Regularization Operators to Support Vector Kernels
Alexander J. Smola,Bernhard Schölkopf +1 more
- 01 Dec 1997
- Vol. 10, pp 343-349
TL;DR: It is proved that the Green's Functions associated with regularization operators are suitable Support Vector Kernels with equivalent regularization properties and a large number of Radial Basis Functions namely conditionally positive definite functions may be used as Support Vector kernels.
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Abstract: We derive the correspondence between regularization operators used in Regularization Networks and Hilbert Schmidt Kernels appearing in Support Vector Machines More specifically, we prove that the Green's Functions 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 conditionally positive definite functions may be used as Support Vector kernels
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References
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The Nature of Statistical Learning Theory
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- 01 Jan 1995
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