Advanced Topics in Machine Learning

Created April 2017

Dirk - André Deckert

Mathematical Institute, LMU Munich, deckert@math.lmu.de
http://www.math.lmu.de/light-and-matter

1 Location and Time

2 News

3 Program

Date Title Speaker
03.05.17 no seminar -
10.05.17 PAC Learning Model (blackboard, notes) Francesco Romano
17.05.17 VC-Dimension (blackboard talk, notes) Jukia Kraus
24.05.17 Boosting (blackboard talk) Christoph Becker
31.05.17 word2vec (slides) Yannick Couzinié
07.06.17 no seminar -
14.06.17 no seminar -
21.06.17 Unsupervised Learning (slides) Shane Shang
28.06.17 Haar Cascades (slides) Nora Kassner
05.07.17 Reinforcement Learning (slides) Christian Hanauer
12.07.17 Recurrent Neural Networks (blackboard talk) Dominik Meindl
19.07.17 no seminar -
27.07.17 no seminar -

4 Suggestion for topics

  1. Mathematical background

  2. PAC Learning Model

  3. Complexity Analysis and VC-Dimension

  4. Complexity analysis of support vector machines

  5. Boosting methods

  6. Approximation

  7. Architecture

  8. Deep learning and convolution networks

  9. Neural network training

  10. Training of support vector machines

  11. Recurrent networks

  12. Unsupervised learning

  13. Reinforcement learning

  14. Special topics

  15. Neural Turing machines

  16. Image style transfer

  17. Real-time face recognition with Haar cascades

  18. Natural language processing

  19. Parts of speech tagging

  20. word2vec

  21. doc2vec