== Block-Seminar "Hot Topics in Machine Learning" ==

The Hot Topics Seminar is an optional course in the module "Machine Learning - Theory and Applications" and is worth 3 LP (3 ECTS credits). 

In the general case, it is not possible to take the Hot Topics Seminar as a standalone course. There are possible exceptions to this (e.g. it complements another ML or related course you are taking in parallel). In that case, a special request needs to be made. 

=== Termine und Informationen ===

||'''Erster Termin für Themenvergabe'''|| Tuesday 08.05.2018 from 09:00 to 10:00 in H 2032 ||
||'''Verantwortlich'''|| Prof. Dr. Klaus-Robert Müller ||
||'''Dozent:''' || Gregoire Montavon, gregoire.montavon@tu-berlin.de ||
||'''Sprache'''|| Englisch ||
||'''Anrechenbarkeit'''|| Wahlpflicht LV im Modul Maschinelles Lernen II (Informatik M.Sc.) ||
||'''ISIS''' || https://isis.tu-berlin.de/course/view.php?id=13338 ||

This seminar takes a closer look at a mix of hot topics in machine learning including, but not limited to: deep learning, interpretable machine learning, optimal transport, reinforcement learning, machine learning in physics.

Students will read, understand, evaluate and present selected research papers. At the end of the semester, each student will present his/her topic in a 20 min talk (+ 5-10 min questions) in English. Students are required to attend the entire seminar.