Statistical Learning

Dozent: Michael Vogt

Übungsleiter: Manuel Rosenbaum

Allgemeine Informationen:

Vorlesung:	2 h (weitere Informationen siehe Moodle/LSF)
Übung:	1 h (weitere Informationen siehe Moodle/LSF)
Inhalt:	1. Classification and Regression Problems - Statistical decision theory - Binary classification - Logistic regression 2. Technical Tools - Exponential inequalities - Concentration inequalities - Subgaussian random variables 3. Uniform Convergence and Generalization - Classification with 0-1-loss - Convex relaxation for classification - Regression 4. Neural Networks - Definition of deep neural networks - Statistical model - Generalization bounds based on Rademacher complexity - Approximation theory - Convergence rates