Vapnik V.N. An Overview of Statistical Learning Theory

IEEE Transactions on Neural Networks, Vol. 10, No. 5, Sept 1999. — p. 988-999.This article presents a very general overview of statistical learning theory including both theoretical and algorithmic aspects of the theory. The goal of this overview is to demonstrate how the abstract learning theory established conditions for generalization which are more general than those discussed in classical statistical paradigms and how the understanding of these conditions inspired new algorithmic approaches to function estimation problems.