This chapter contains sections titled: Introduction, Overview of Statistical Learning Theory, Regularization Networks, Support Vector Machines, SRM for RNs and SVMs, A Bayesian Interpretation of Regularization and SRM?, Connections Between SVMs and Sparse Approximation Techniques, Remarks, Acknowledgments