Webrelaunch 2020

(Winter Semester 2023/24)

Ilias course: https://ilias.studium.kit.edu/goto.php?target=crs_2182507

Machine learning is ubiquitous in modern data science. The mathematical foundation of machine learning is at the intersection of optimization, approximation theory and statistics. In this seminar we study several aspects and methods of machine learning from the numerical as well as from the statistical perspective.

The seminar is jointly organized by Martin Frank (SCC), Sebastian Krumscheid (SCC) and Mathias Trabs (STOCH).

Preliminary meeting: 9:45, 27 July 2023, Room 3.061 (math building)

Topics covered in the seminar include:

  • Reinforcement Learning
  • Stochastic optimization
  • Kernel methods
  • Neural networks