525
Comment:
|
766
|
Deletions are marked like this. | Additions are marked like this. |
Line 15: | Line 15: |
=== Topics === Embedding Stationary Subspace Analysis Auto-encoders Canonical Correlation Analysis Kernel methods for structured data Neural networks for structured data Structured output learning One-class SVMs Bioinformatics |
Maschinelles Lernen - Theorie und Anwendung
General Information
Maschinelles Lernen - Theorie und Anwendung is a 9 LP (9 ECTS) credits module.
Lecture |
Tuesdays, 10 - 12 |
Room |
MAR 0.015 |
Exercise session |
Tuesdays, 12 - 14 |
Room |
MAR 0.015 |
Trainers |
Prof. Dr. Klaus-Robert Müller (Responsible) |
Gregoire Montavon |
|
Contact |
|
ISIS |
Topics
Embedding Stationary Subspace Analysis Auto-encoders Canonical Correlation Analysis Kernel methods for structured data Neural networks for structured data Structured output learning One-class SVMs Bioinformatics