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Instructors: Prof. Dr. rer. nat. Marc Pfetsch; Oliver Habeck
Event type:
Lecture & Exercise
Org-unit: Dept. 04 - Mathematics
Displayed in timetable as:
Opt. Machine Learning
Subject:
Crediting for:
Hours per week:
3
Language of instruction:
German and English
Min. | Max. participants:
- | -
Course Contents:
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.
Preconditions:
recommended: Introduction to Optimization; useful: Discrete Optimization or Nonlinear Optimization
Online Offerings:
moodle
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