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Institute for Machine Learning
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Theoretical Concepts of Machine Learning (1UE)

Course no.: 365.042 (group 1) / 365.100 (group 2) / 365.244 (group 3) / 365.245 (group 4)
Lecturers: Johannes Kofler (kofler@ml.jku.at), Markus Holzleitner (holzleitner@ml.jku.at)

 

Motivation:

This practical course complements the lecture Theoretical Concepts of Machine Learning and aims at practicing the concepts and methods acquired in the lecture.

Topics:

  • Generalization error
  • Bias-variance decomposition
  • Error models
  • Model comparisons
  • Estimation theory
  • Statistical learning theory
  • Worst-case and average bounds on the generalization error
  • Structural risk minimization
  • Bayes framework
  • Evidence framework for hyperparameter optimization
  • Optimization techniques
  • Theory of kernel methods