From 2 November 2020, the autumn semester 2020 will take place online. Exceptions: Courses that can only be carried out with on-site presence.
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252-5051-00L  Advanced Topics in Machine Learning

SemesterAutumn Semester 2015
LecturersJ. M. Buhmann, T. Hofmann, A. Krause
Periodicityyearly recurring course
Language of instructionEnglish



Catalogue data

AbstractIn this seminar, recent papers of the pattern recognition and machine learning literature are presented and discussed. Possible topics cover statistical models in computer vision, graphical models and machine learning.
ObjectiveThe seminar "Advanced Topics in Machine Learning" familiarizes students with recent developments in pattern recognition and machine learning. Original articles have to be presented and critically reviewed. The students will learn how to structure a scientific presentation in English which covers the key ideas of a scientific paper. An important goal of the seminar presentation is to summarize the essential ideas of the paper in sufficient depth while omitting details which are not essential for the understanding of the work. The presentation style will play an important role and should reach the level of professional scientific presentations.
ContentThe seminar will cover a number of recent papers which have emerged as important contributions to the pattern recognition and machine learning literature. 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. Frequently, papers are selected from computer vision or bioinformatics - two fields, which relies more and more on machine learning methodology and statistical models.
LiteratureThe papers will be presented in the first session of the seminar.

Performance assessment

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

Learning materials

 
Main linkInformation
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
252-5051-00 SAdvanced Topics in Machine Learning Special students and auditors need a special permission from the lecturers.2 hrs
Tue16-18CAB H 52 »
Thu16-18CHN G 22 »
J. M. Buhmann, T. Hofmann, A. Krause

Groups

No information on groups available.

Restrictions

General : Special students and auditors need a special permission from the lecturers

Offered in

ProgrammeSectionType
Certificate of Advanced Studies in Computer ScienceSeminarsWInformation
Computer Science MasterSeminar Visual ComputingWInformation
Robotics, Systems and Control MasterCore CoursesWInformation
Statistics MasterSeminar or Semester PaperWInformation