Statistical Learning

Prof. Dr. Christian Bender

Winter Semester 2024/2025

Recommended prerequisites

Knowledge of measure-theoretic probability theory at the level of the mathematics course Stochastik I.

Lectures

Thursdays, 12.15 - 13.45 pm, building E2 4, HS IV (room 1.15)

Tutorials

Fridays, 12.15-13.45 pm, building E2 4, Seminarraum 9
8 Nov 2024, 22 Nov 2024, 6 Dec 2024, 10 Jan 2025, 24 Jan 2024, 7 Feb 2025

Exam

Oral exam at the end of the semester.

Course material

The course material can be found on the learning management system Moodle. If you are interested to attend the course, please ask for the enrolment key at your earliest convenience via email to:

bender [at] math.uni-sb.de

Moodle enrolment

Introduction to the regression problem and to pattern recognition
Local averaging methods (e.g., kernel smoothing, k-nearest neighbor)
Concentration inequalities (Hoeffding, Bernstein)
Sample splitting
Empirical risk minimization
Vapnik-Chervonenkis inequality
Combinatorial aspects of the Vapnik-Chervonenkis theory