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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.
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||'''Erster Termin für Themenvergabe'''|| TBA ||
||'''Termin für Vorträge'''|| TBA ||
||'''Erster Termin für Themenvergabe'''|| Tuesday 08.05.2018 from 09:00 to 10:00 in H 2032 ||
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||'''ISIS''' || https://isis.tu-berlin.de/course/view.php?id=13338 ||
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This seminar takes a closer look at a mix of hot topics in machine learning including, but not limited to: attention based models, quantum machine, deep reinforcement learning, privacy and machine learning, .... 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.
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Students will read, understand, evaluate and present selected research papers on deep learning. At the end of the semester, each student will present his/her topic in a 20 min talk (+ 5-10 min questions) in English.
The dates for this seminar are fixed
. Students are required to attend the entire seminar.
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.

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.

IDA Wiki: Main/SS18_HOT (last edited 2018-05-31 13:29:25 by GrégoireMontavon)