STAT 538

Statistical Learning: Modeling, Prediction, and Computing
3.0 credits

Course Description

Reviews optimization and convex optimization in its relation to statistics. Covers the basics of unconstrained and constrained convex optimization, basics of clustering and classification, entropy, KL divergence and exponential family models, duality, modern learning algorithms like boosting, support vector machines, and variational approximations in inference. Prerequisite: experience with programming in a high level language. Offered: W.

Upcoming Time Schedule

Winter, 2022

SLN/Section Time Location Instructor
20528 A
Open

T T 10:00AM - 11:20AM

GLD 117

GRADE OF AT LEAST 3.0 IN STAT 535 OR CSE 546 IS REQUIRED.