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WS 2011/2012 (310003)

Machine Learning: Basic Course

Lecture and Tutorial
Prof. Dr. Laurenz Wiskott
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Lecture (2 SWS, 2 credit points): Tuesdays 12:00-13:30 o'clock in the larger INI seminar room NB 3/57. First time 11.10.2011.
Tutorial (2 SWS, 4 credit points): Tuesdays 10:15-11:45 o'clock in the larger INI seminar room NB 3/57. First time 18.10.2011.

Exam 1: Wednesday 2012-03-21 10:00-12:30 in HZO 90.
Exam 2: Wednesday 2012-09-19 11:00-13:30 in NB 2/99.
For the exams, only pen and ruler are permitted plus a handwritten formulary (Formelsammlung) of one page DIN A4 (only one side, not two sides written). Paper will be provided.


Description: This course covers a variety of unsupervised and supervised methods from machine learning such as principal component analysis, independent component analysis, vector quantization, clustering, self-organizing maps, growing neural gas, Bayesian theory and graphical models, support vector machines, optimization.

Language: The course will be given in English upon request.

Literature: For many topics a script will be available.

Prerequisites: Good command of linear algebra and calculus.


Schedule and course material

# date topic
- UNSUPERVISED LEARNING
1 11.10.2011 Introductory remarks
Principal component analysis I
2 18.10.2011 Principal component analysis II
3 25.10.2011 Principal component analysis III
Fisher discriminant analysis
4 08.11.2011 Independent component analysis I
5 15.11.2011 Independent component analysis II
6 22.11.2011 Vector quantization
7 29.11.2011 Clustering
8 06.12.2011 Self Organizing Maps
Slow Feature Analysis
9 13.12.2011 Bayesian inference
10 20.12.2011 Inference in Bayesian networks
11 10.01.2012 Inference in Gibbsian networks
12 17.01.2012 Learning in Bayesian networks
- REINFORCEMENT LEARNING
13 24.01.2012 Reinforcement Learning
14 31.01.2012 Summary and Review of All Lectures

Laurenz Wiskott, http://www.ini.rub.de/PEOPLE/wiskott/