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