Learning Theory

Content

• • Application of McDiarmid's inequality

  • Infinite many hypothesis

  • Uniform convergence bounds

  • PAC bound for estimation error

  • Structural risk minimzation

• Vapnik Chervonenkis dimension

  • Shattering

  • Growth Function

  • Sauer's lemma

  • Vapnik-Chervonenkis inequality

  • Vapnik-Chervonenkis theorem

Supplementary material

• Slides in PDF.

Recommended papers

• L. Devroye, L. Gyorfi, G. Lugosi: A Probabilistic Theory of Pattern Recognition. Springer, New York, 1996.

• L. Gyorfi (editor): Principles of Nonparametric Learning, Springer-Verlag Wien New York, 2002

• L. Gyorfi, M. Kohler, A. Krzyzak, H. Walk: A Distribution-Free Theory of Nonparametric Regression, Springer-Verlag, New York, 2002

• A. Tsybakov: Introduction to Nonparametric Estimation, Springer Series in Statistics, 2008

• Robert D. Nowak: Lecture notes about Statistical Learning Theory