Theoretical Concepts of Machine Learning (1UE)
| Course no.: | 365.042 |
| Lecturer: | Günter Klambauer |
| Times/locations: | Mon 14:30-15:15, room tba Start: Thu, March 8, 2018 |
| Mode: | UE, 1h, weekly |
| Registration: | KUSSS |
Motivation:
This practical course complements the lecture Theoretical Concepts of Machine Learning and aims at practicing the concepts and methods acquired in the lecture. Topics:- Generalization error
- Bias-variance decomposition
- Error models
- Model comparisons
- Estimation theory
- Statistical learning theory
- Worst-case and average bounds on the generalization error
- Structural risk minimization
- Bayes framework
- Evidence framework for hyperparameter optimization
- Optimization techniques
- Theory of kernel methods