Seminar: High-dimensional Probability - Details

Seminar: High-dimensional Probability - Details

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General information

Course name Seminar: High-dimensional Probability
Course number MTH-1410
Semester WS 2024/25
Current number of participants 2
Home institute Stochastik und ihre Anwendungen
Courses type Seminar in category Teaching
Pre-requisites Probability Theory, Linear Algebra
Veranstaltung findet in Präsenz statt / hat Präsenz-Bestandteile Yes
Hauptunterrichtssprache englisch
Literaturhinweise High-Dimensional Probability, An Introduction with Applications in Data Science by R. Vershynin (Cambridge University Press)
https://www.math.uci.edu/~rvershyn/papers/HDP-book/HDP-book.html#

Foundations of Data Science by A. Blum, J. Hopcroft, and R. Kannan (Cambridge University Press)
https://home.ttic.edu/~avrim/book.pdf

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Comment/Description

In the big data era, data live in very high-dimensional spaces and sometimes our intuition from two- or three-dimensional space suprisingly fails when it comes to high dimensions. It is therefore important to develop a probabilistic toolbox to understand and analyze more efficiently random objects in high-dimensional spaces. High-Dimensional probability is an exciting mathematical theory that studies the behavior of random vectors, random matrices, random subspaces and random processes and has applications in statistics, theoretical computer science, signal processing, optimization, machine learning, and more.