Students will obtain an in-depth introduction to unsupervised learning methods: models, theories, and application examples.
Unsupervised Learning models, such as self-organizing maps, growing hierarchical structures, cellular automata, ant colony optimisation, ...
Lecture Dates:
tba: Introduction, SOM - part 1: Basic principles, architecture, training methods
tba: SOM - part 2: Visualization, Evaluation, Applications
tba: Genetic Algorithms & Cellular Automata
tba: Multiagentensystems
tba: general aspects of self-organization
