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CMU
Alex Smola
Barnabas Poczos
Ina Fiterau
Junier Oliva
Leila Wehbe
Mu Li
Xuezhi Wang
MLD
CMU

Risk Minimization and Tail Bounds

Introduction to Machine Learning - 10-701/15-781

Content

  • Risk and loss

    • Loss functions

    • Risk

    • Empirical risk vs True risk

    • Empirical Risk minimization

  • Underfitting and Overfitting

  • Examples

    • Classification

    • Regression

Supplementary material

  • Slides in PDF.

  • 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

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