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.

Current Time Schedule

Winter, 2025

SLN/Section Time Location Instructor
20777 A
Open

M W 9:00AM - 10:20AM

PCAR 295

Armeen Taeb

JOINT WITH STAT 538B.

 

 

20778 B
Open

M W 9:00AM - 10:20AM

PCAR 295

Armeen Taeb

JOINT WITH STAT 538A. GRADS ONLY STAT MS FEE-BASED STUDENTS ONLY.