Universität Wien
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250049 VO Stochastic Algorithms (2024S)

6.00 ECTS (4.00 SWS), SPL 25 - Mathematik
Moodle

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

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 05.03. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 06.03. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 13.03. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 19.03. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 20.03. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 09.04. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 10.04. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 16.04. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 17.04. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 23.04. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 24.04. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 30.04. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 07.05. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.05. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 14.05. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 15.05. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 21.05. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 22.05. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 28.05. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 29.05. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 04.06. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 05.06. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 11.06. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 12.06. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 18.06. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 19.06. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 25.06. 13:15 - 14:45 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 26.06. 09:45 - 11:15 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

In this course, we explore a range of algorithms in optimization, computer science, and machine learning, all sharing a distinctive common feature — the presence of randomness. We will understand how to analyze such algorithms, and why randomness can be so helpful.

Prerequisites for the course:
Necessary: basic linear algebra, analysis, probability theory.
Recommended: nonlinear optimization (at least students should be familiar with convexity).

Assessment and permitted materials

Oral exam on the entire course material at the end of the course, no materials permitted.

To choose the time slot for the exam follow the link. Please note that each time slot has a maximum capacity of 7 people.
https://www.termino.gv.at/meet/b/0b778b64dc18347fb44cefd086681bf1-327608

If none of those time slots work for you, write to me individually.
The exam takes place at my office, 7.136.

Minimum requirements and assessment criteria

Satisfactory answer to questions about course and solution of problems.

Examination topics

Entire course material.

Reading list

Association in the course directory

MAMV; MSTV;

Last modified: We 05.03.2025 14:46