Semiparametric Support Vector and Linear Programming Machines
Smola, Alex J., Frieß, Thilo-Thomas, Schölkopf, Bernhard
–Neural Information Processing Systems
In fact, for many of the kernels used (not the polynomial kernels) like Gaussian rbf-kernels it can be shown [6] that SV machines are universal approximators. While this is advantageous in general, parametric models are useful techniques in their own right. Especially if one happens to have additional knowledge about the problem, it would be unwise not to take advantage of it.
Neural Information Processing Systems
Dec-31-1999