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401-5006-23L 2 Credits DR D-MATH

Probabilistic Methods in Analysis

Lecturers & Examiners: Prof. Dr. Shahar Mendelson
Doctoral students of I-Math (UZH) need to send an email to Jessica Bolsinger ( ) with the course number. The email should have the subject „Graduate course registration (ETH)“.
VVZ CR n/a

Last Updated: 2026-02-05 16:22:19

Abstract

Nachdiplom lecture

Content

The aim of the course is to explore several questions in Asymptotic Geometric Analysis that share a rather surprising feature: their formulation has nothing to do with Probability Theory but their solution is heavily based on probabilistic arguments. I will use those problems to illustrate two important ideas: that randomness can be used to expose "hidden structures"; and that structure often appears in "extremal situations" (both these rather vague statements will be made clear during the course). Along the way, I will develop the necessary machinery which is important in its own right: it is of constant use in many areas of modern mathematics, statistics and computer science. Although I will try to make the course as self-​contained as possible, it will require mathematical maturity. Knowledge of some Functional Analysis, measure and integration and probability theory is highly recommended.

General Information

Language
English
Levels
DR

Examination

Type
ungraded semester performance

Course Components

Type Title Time & Place Hours
lecture Probabilistic Methods in Analysis
If you would like to attend the lecture please register by 24 February. For the registration form see
  • Wed 10:15-12:00 (HG G 43)
26 h semesterly

Offered In