Extended Seminar – Systems and Machine Learning

The seminar will be jointly held by Profs. Carsten Bin­nig, Kristian Kersting, Mira Mezini and Andreas Koch.

Topics will include both ML for Systems as well as Systems for ML, e.g., using ML to improve database and software engineering systems but also papers leveraging novel hardware or other techniques to improve machine learning systems.

The top­ics will be as­signed based on an on-line bid­ding pro­cess, which will be opened after the kick-off.​ The final as­sign­ment will be made a week later.

Quick Links

Course Material (Moodle) Registration (Tucan)

Organization

Course Infos

Below, you find some general information about the seminar. For all information regarding this year's seminar (including important dates) please check the moodle course linked above.

Prerequisites

It is not necessary to have prior knowledge in artificial intelligence, but prior knowledge in software/hardware systems and machine learning is helpful.​ Participation is limited to 20 students.​

For further questions feel free to send an email to dm@​cs.​tu-darmstadt.​de. No prior registration is needed, however, please still send us an email so that we are able to estimate beforehand the number of participants, and have your E-mail address for possible announcements.​ Also make sure that you are registered in TUCaN.

Ex­tend­ed Sem­i­nar

What is “Ex­tend­ed” about this sem­i­nar? Stu­dents are ex­pect­ed to give a short talk that not only covers the assigned paper but also related work and relevant background. It is mandatory to discuss your presentation with us before the seminar.

After each talk there will be a discussion phase in which students are expected to participate actively. In particular, every student has to moderate one of these discussions and in addition write three reviews for other seminar papers to enable an in-depth discussion of each presented paper. We will provide review forms for this.

Be­cause this is more work for stu­dents, stu­dents re­ceive 4 CPs for Ex­tend­ed Sem­i­nars (in­stead of 3 CPs for reg­u­lar sem­i­nars).

Grad­ing

The slides, the pre­sen­ta­tion, the an­swers given to ques­tions in your talk will in­flu­ence the over­all grade, as will the reviews and your moderation of the discussion.​ Further­more, it is ex­pect­ed that stu­dents ac­tive­ly par­tic­i­pate in the dis­cus­sions, and this will also be part of the final grade.

To achieve a grade in the 1.​x range, the talk and reviews need to ex­ceed the recita­tion of the given ma­te­ri­al and in­clude own ideas, own ex­pe­ri­ence or even examples/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.​ For the write-ups it is im­por­tant that they pro­vide a co­her­ent view (like a sur­vey paper), and do not sim­ply con­sist of a con­cate­na­tion of four paper sum­maries.

Sched­ule

See schedule on Moodle (link above)

Topics

All pa­pers should be avail­able on the in­ter­net or in the ULB.​ Note that Springer link often only works on cam­pus net­works (some­times not even via VPN). If you can­not find a paper, con­tact us.

See moodle course for current topics.