Seminar aus Data Mining und Maschinellem Lernen

Extreme Classification

The Seminar is available in Tucan right here.

When and where?

The kick-off meeting was on Tuesday, the 12th of April at 17:10 in A213. The regular meetings will take place on Wednesdays at 17:10 in Room S1 03/12 (main building). 


The topics for the talks will be assigned in the kick-off meeting. For further questions feel free to send an email to No prior registration is needed, however, please stlll send us an email so that we are able to estimate beforehand the number of participants.


In the course of this seminar we will try to get an overview on the current state of research in a domain. This year's topic will be Extreme Classification, i.e. methods and approaches for handling multi-class and multi-label classification problems with thousands and millions of categories. We will concentrate on recent papers published in workshops, journals, and conferences. Some entry points for interesting references are the eXtreme Classification workshops (2013, 2015, 2015) and the Extreme Classification repository.
The students are expected to give a 30 minute talk on the material they are assigned, followed by 15 minutes of questions. The content of the talk should exceed the scope of the paper, and demonstrate that a thorough understanding of the material was achieved. See also our general advices on giving talks.


The presentation slides are only accessible through the university network (you may use VPN to access them).


The talks are expected to be accompanied by slides. In case you do not own a laptop, please send us the slides in advance, so that we can prepare and test the slides. The talk and the slides are allowed to be both english or german, but we strongly encourage the students to give the talk in english.


The slides, the presentation and the question and answers section of the talk will influence the overall grade. Furthermore, it is expected of the students to participate in the discussions. There is no need for a written verdict of the material.
Most importantly, the autonomous elaboration on the material will influence the grade. To achieve a grade in the 1.x range, the talk needs to exceed the contentual recitation of the given material and include own ideas, own experience or even demos. An exact recitation of the papers will lead to a grade in the 2.x range. A weak presentation and lack of engagement in the discussions may lead to a grade in the 3.x range, or worse.
Please read also very carefully our guidelines for giving a talk.

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Knowledge Engineering Group

Fachbereich Informatik
TU Darmstadt

S2|02 D203
Hochschulstrasse 10

D-64289 Darmstadt

Telefon-Symbol+49 6151 16-21811
Fax-Symbol +49 6151 16-21812

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