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 DereichProf. Dr. Zakhar Kabluchko
KommVV:

This event in the course overview

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.