View on GitHub


Website for the Seminar on Learning Theory, taught WS18/19 by Michael Kamp and Pascal Welke

This website is the written documentation of the Seminar Principles of Data Mining and Learning Algorithms – „Learning Theory“ MA-INF 4209, taught at the University of Bonn during the Winter Termin 2018/2019 by Pascal Welke & Michael Kamp.

The seminar is based on the book „Understanding Machine Learning“ by Shai Shalev-Shwartz and Shai Ben-David. Below, you find the write-ups of our sessions.

Session Presenter Book Chapter Link Screencast
1 Michael Kamp 1 & 2 Introduction and Gentle Start Screencast
2 Mikhail Borisov 3 & 4 APAC Learning and Uniform Convergence Screencast
3 Lukas Drexler 5.1 No Free Lunch Theorem Screencast
3 Lukas Drexler 5.2 Error Decomposition Screencast
3 Lukas Drexler 6 VC-Dimension Screencast
4 Oliver Kiss 6 Addition VC-Dimension Screencast
4 Oliver Kiss 7 Nonuniform Learnability Screencast
4 Oliver Kiss 6 & 7 Q&A  
5 Maximilian Thiessen 7 MDL and Other Notions of Learnability Screencast
5 Pascal Welke 7 An Alternative Proof for Thm 7.2  
5 Maximilian Thiessen 8 The Runtime of Learning Screencast
6 Sara Hahner 26 Rademacher Complexity Screencast
7 Zhuofan Liu 30 & 31 Compression Bounds & PAC-Bayes Screencast
X All All Collected Errata