PROBABILISTIC MACHINE LEARNING

STA 561D

Introduction to concepts in probabilistic machine learning with a focus on discriminative and hierarchical generative models. Topics include directed and undirected graphical models, kernel methods, exact and approximate parameter estimation methods, and structure learning. Instructor: Staff

Day / Time: 

M 04:40 PM-05:55 PM

Location: 

Hudson 216

Instructor: 

Mukherjee, Sayan

Section: 

07D