Seminar on High-Dimensional Probability and Applications in Data Science
With the fast-paced evolution of data sciences, a deeper grasp of probabilistic methods is essential. This course studies high-dimensional probability, with applications in data sciences, focusing on random vectors, matrices, and projections in large dimensions.
The lectures (2 hours per week) are based on the book
High-Dimensional Probability and Applications in Data Science by Roman Vershynin [More]
Prerequisites: A rigorous course in probability theory and a solid foundation in undergraduate linear algebra.
Lectures: Friday 12:15-14. Place: NHA, room UE26.
First lecture is August 30.
(Last lecture November 29.)
Published Aug. 5, 2024 7:36 AM
- Last modified Aug. 5, 2024 1:22 PM
