MATH 6230X: High-Dimensional Probability and Linear Algebra for Machine Learning
(Cross-listed with EE 6230X).
Credits: 3. Contact Hours: Lecture 3.
Repeatable.
Key topics from non-asymptotic random matrix theory: Bounds on minimum and maximum singular values of many classes of high-dimensional random matrices, and on sums of a large number of random matrices. Chaining. Other linear algebra and probability concepts commonly used in Theoretical Machine Learning research. Discussion of recent papers in this area.