Universität Wien
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040694 UK Nonparametric Inference and Resampling (MA) (2026S)

5.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
REMOTE
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 03.03. 17:00 - 17:45 Digital
  • Thursday 05.03. 11:30 - 13:00 Digital
  • Tuesday 10.03. 17:00 - 17:45 Digital
  • Tuesday 17.03. 17:00 - 17:45 Digital
  • Thursday 19.03. 11:30 - 13:00 Digital
  • Tuesday 24.03. 17:00 - 17:45 Digital
  • Thursday 26.03. 11:30 - 13:00 Digital
  • Tuesday 14.04. 17:00 - 17:45 Digital
  • Thursday 16.04. 11:30 - 13:00 Digital
  • Tuesday 21.04. 17:00 - 17:45 Digital
  • Thursday 23.04. 11:30 - 13:00 Digital
  • Tuesday 28.04. 17:00 - 17:45 Digital
  • Thursday 30.04. 11:30 - 13:00 Digital
  • Tuesday 05.05. 17:00 - 17:45 Digital
  • Thursday 07.05. 11:30 - 13:00 Digital
  • Tuesday 12.05. 17:00 - 17:45 Digital
  • Tuesday 19.05. 17:00 - 17:45 Digital
  • Thursday 21.05. 11:30 - 13:00 Digital
  • Tuesday 26.05. 17:00 - 17:45 Digital
  • Thursday 28.05. 11:30 - 13:00 Digital
  • Tuesday 02.06. 17:00 - 17:45 Digital
  • Tuesday 09.06. 17:00 - 17:45 Digital
  • Thursday 11.06. 11:30 - 13:00 Digital
  • Tuesday 16.06. 17:00 - 17:45 Digital
  • Thursday 18.06. 11:30 - 13:00 Digital
  • Tuesday 23.06. 17:00 - 17:45 Digital
  • Thursday 25.06. 11:30 - 13:00 Digital
  • Tuesday 30.06. 17:00 - 17:45 Digital

Information

Aims, contents and method of the course

Empirical risk minimization
Concentration Inequalities
Entropy and Chaining
Nonparametric Regression
Model Selection
Bootstrap

Course will take place online (Stream)

Assessment and permitted materials

Exercises, two or three sheets.

The use of AI tools (e.g. ChatGPT) for the production of texts is only permitted if they are expressly requested by the course leader (e.g. for individual work tasks).

Minimum requirements and assessment criteria

Minimum of 50% is required to pass.

Examination topics

All topics covered in class.

Reading list

S. Boucheron, G. Lugosi und P. Massart. Concentration inequalitites. A nonasymptotic theory of independence. Oxford University Press, Oxford, 2013.
P. Massart. Concentration inequalitites and model selection. Springer, Berlin, 2007.
A. Tsybakov. Introduction to nonparametric estimation. Springer, 2009.
L. Wasserman. All of nonparametric statistics. Springer, 2006.

Association in the course directory

Last modified: Mo 27.07.2026 09:26