252-4811-00L  Machine Learning Seminar

SemesterAutumn Semester 2022
LecturersV. Boeva, T. Hofmann, E. Krymova
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.


252-4811-00 SMachine Learning Seminar
Kick-off Meeting: September 23, 2022; 12-13; CAB H52

Saturday sessions: November 12 and 26, December 3, 2022; from 08:30 - 13:00; CAB H52
2 hrs
23.09.12:15-13:00CAB H 52 »
V. Boeva, T. Hofmann, E. Krymova

Catalogue data

AbstractSeminal and recent papers in machine learning are presented and discussed.
ObjectiveThe seminar familiarizes students with advanced and recent ideas in machine learning. Original articles have to be presented, contexctualized, and critically reviewed. The students will learn how to structure a scientific presentation in English which covers the key ideas of a scientific paper.
ContentThe seminar will cover a number of recent papers which have emerged as important contributions in the machine learning research community. The topics will vary from year to year but they are centered on methodological issues in machine learning like new learning algorithms, ensemble methods or new statistical models for machine learning applications.
LiteratureThe papers will be presented and allocated in the first session of the seminar.
Prerequisites / NoticeBasic knowledge of machine learning as taught in undergraduate courses such as "252-0220-00 Introduction to Machine Learning" are required.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits2 credits
ExaminersV. Boeva, T. Hofmann, E. Krymova
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.


No information on groups available.


Places24 at the most
PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupComputer Science BSc (252000)
Waiting listuntil 03.10.2022

Offered in

Computer Science BachelorSeminarWInformation