Statistical Learning Theory

Aus VISki
Wechseln zu: Navigation, Suche

Overview

Abstract

The course covers advanced methods of statistical learning: Statistical learning theory;variational methods and optimization, e.g., maximum entropy techniques, information bottleneck, deterministic and simulated annealing; clustering for vectorial, histogram and relational data; model selection; graphical models.

Objective

The course surveys recent methods of statistical learning. The fundamentals of machine learning as presented in the course "Introduction to Machine Learning" are expanded and in particular, the theory of statistical learning is discussed.

Summaries

Exam Solutions

  • no exam solutions here yet

Additional Material

Literature

  • no literature here yet