STAT 578

Fall 2023

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Credit: 4 hours.

May be repeated if topics vary. Prerequisite: Consent of instructor.

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CRN Type Section Time Day Location Instructor Section Details
71915
Lecture-Discussion
SC
12:00PM -12:50PM
MWF
106B8 Engineering Hall
Chatterjee, S
Part of Term:
1
Date Range:
08/21/23-12/06/23
Section Title:
Intro to High Dimensional Prob
Section Info:
Title: An Introduction to High Dimensional Probability with Applications to Data Science Description: This course builds probabilistic foundations for theoretical research in modern data science. You will learn some methods that form an essential toolbox for anyone looking to do mathematical work in machine learning, theoretical computer science, theoretical statistics, signal processing, etc. The course is suitable for first/second year PhD students in mathematics, statistics, computer science, and electrical engineering. A solid background in undergraduate linear algebra, real analysis, and probability theory are minimum prerequisites. Some familiarity with metric, Hilbert and normed spaces is a plus, but is not required. Knowledge of measure theory is not required. For Statistics course registration information: go.illinois.edu/StatisticsRegistration.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
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