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: Heller, Mukherjee, or Reeves

Day / Time: 

M 11:45 AM-01:00 PM

Location: 

Physics 235

Instructor: 

Rudin, Cynthia

Section: 

03D