Chapter

Advanced Lectures on Machine Learning

Volume 3176 of the series Lecture Notes in Computer Science pp 169-207

Introduction to Statistical Learning Theory

  • Olivier BousquetAffiliated withMax-Planck Institute for Biological Cybernetics
  • , Stéphane BoucheronAffiliated withLaboratoire d’Informatique, Université de Paris-Sud
  • , Gábor LugosiAffiliated withDepartment of Economics, Pompeu Fabra University

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Abstract

The goal of statistical learning theory is to study, in a statistical framework, the properties of learning algorithms. In particular, most results take the form of so-called error bounds. This tutorial introduces the techniques that are used to obtain such results.