MSc seminar on probability theory


Dates: Tuesday, 4pm - 6pm, SRZ 117, expected dates in the "talks" section.

Prof. Dr. Gerold Alsmeyer, Prof. Dr. Zakhar Kabluchko

Assistance: Philipp Godland

Entry of this course in the course catalogue
Entry of this course in the course catalogue

Course syllabus:

This course covers topics from various areas in probability theory. Among these are:

  • Statistical Learning Theory
  • Infinite Divisibility
  • Mod-φ Convergence
  • Brownian Motion

[A] Alsmeyer, G. (2017). Wahrscheinlichkeitstheorie (2. Auflage). Skripten zur Mathematischen Statistik 40, Universität Münster.
[FMN] Féray, V., Méliot, P.-L., Nikeghbali, A. (2016). Mod-φ Convergence: Normality Zones and Precise Deviations. Springer.
[MP] Mörters, P., Peres, Y. (2010). Brownian Motion. Cambridge.(Errata)
[MS] Mendelson, S., Smola, A. J. (2003). Advanced Lectures on Machine Learning. Springer.

[FMN] and [MS] are collected in a special section for this course in the library. Chapter 12 from [A] is hyperlinked below.

Course assessment:

The seminar can be passed by handing in a written report, successfully giving a talk and by constant participation. The length of the talks is supposed to lie between 60 and 75 minutes.

Reports: Please hand in the report as a PDF by no later than 2 weeks before the talk.
Please note: Do not forget to enrol for the course in QISPOS.


Date Name Topic Source Advisor
23.04.2019 Jonas Scharfenberger Introduction to Statistical Learning Theory [MS] Alsmeyer
30.04.2019 David Röckner Infinite Divisibility & Lévy-Khintchine Formula [A], Kapitel 12 [de] Godland
07.05.2019 Arian Beckmann Mod-φ Convergence [FMN], 1.1, 2.1, 3.1 Godland
14.05.2019 Franziska Frederking Fluctuations in the case of lattice distributions [FMN], 3.2, (3.3) Godland
28.05.2019 Felix Albert Fluctuations in the non-lattice case [FMN], 4.1-4.3 Godland
04.06.2019 Thomas Kleine Büning Theory of dependency graphs [FMN], 9.1-9.5 Alsmeyer/Godland
18.06.2019 Lennart Machill The local time of a Brownian Motion [MP], 6.1 Godland