Masterseminar Probability Theory (Alsmeyer, Dereich, Kabluchko)
WS 2022/23
| Date: |
Tuesdays 16:15, SRZ 203 |
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| Dozent: | Prof. Dr. Gerold Alsmeyer, Prof. Dr. Steffen Dereich, Prof. Dr. Zakhar Kabluchko |
| KommVV: | |
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Topic: |
In this seminar, we discuss advanced topics related to probability theory. Topics come from one of the following areas: Stochastic processes Machine learning Stochastic geometry
Possible topics in Machine Learning (referring to the book "Mathematics of Data Science", see material)
M1: Matrix concentration inequalities (Sect. 6.4, p. 91-97)
M2: The Johnson-Lindenstrauss Lemma (Section 9.1, p. 123-130)
M3: Gordon's theorem (Sect. 9.2, p. 130-134) (one might fill up the presentation with additional topics from Sect. 9.3 or include the proof of Slepian's lemma or Thm 9.15) M4: Compressive Sensing (Sect. 10.1, p. 142-148; include motivation of introduction to Sect. 10) Further topics will be posted soon. |