• Course code:63444
  • Credits:5
  • Semester: winter
  • Contents
  • Bayesian methods: Gaussian processes, Dirichlet processes, MCMC methods, variational inference.
  • Deep learning: Boltzmann machines, Autoencoders, Convolutional neural networks.
  • Computational learning theory: PAC learning, VC dimension.
  • Other select topics: multi-kernel learning, multi-task learning, reinforcement learning.
  • Study programmes
  • Distribution of hours per semester
14
hours
lectures
10
hours
laboratory work
  • Professor
Assist. Prof. dr. Aleksander Sadikov
Instructor
Room:R3.69 - Kabinet
details