معلومات المساق

Digital Teaching
Registration for this course will be possible starting on Sept. 20. The teaching type will depend on the corona rules and will be announced.

Lehrinhalte
classification (support vector machines), clustering, matrix completion, sparse regression, lasso, sparse inverse covariance selection, neural networks (deep learning), Markov random fields

Literature
Mitchell: Machine Learning. Mcgraw-Hill 1997
Murphy: Machine Learning: A Probabilistic Perspective, MIT Press 2012
Sra,Nowozin, Wright: Optimization for Machine Learning, MIT Press, 2012
Miroslav Kubat: An Introduction to Machine Learning.Springer, 2015.

Voraussetzungen
recommended: Introduction to Optimization; useful: Discrete Optimization or Nonlinear Optimization