Empirical Process Theory with Applications in Statistics and Machine Learning

Spring semester 2019

General information

Lecturer Sara van de Geer
Lectures Thursday 8-10 HG E 5 >>
Course catalogue data >>

Course content

In this series of lectures, we will start with considering exponential inequalities, including concentration inequalities, for the deviation of averages from their mean. We furthermore present some notions from approximation theory, because this enables us to assess the modulus of continuity of empirical processes. We introduce e.g., Vapnik Chervonenkis dimension: a combinatorial concept (from learning theory) of the "size" of a collection of sets or functions. As statistical applications, we study consistency and exponential inequalities for empirical risk minimizers, and asymptotic normality in semi-parametric models. We moreover examine regularization and model selection.


  • January 22, 2019:
    The first lecture takes place on Thursday February 21, 2019.
  • Course materials