Kernel methods and the exponential family

The success of support vector machine (SVM) has given rise to the development of a new class of theoretically elegant learning machines which use a central concept of kernels and the associated reproducing kernel Hilbert space (RKHS). Exponential families, a standard tool in statistics, can be used to unify many existing machine learning algorithms based on kernels (such as SVM) and to invent novel ones quite effortlessly. A new derivation of the novelty detection algorithm based on the one class SVM is proposed to illustrate the power of the exponential family model in an RKHS. (c) 2005 Published by Elsevier B.V.