COS597C: Advanced Methods in Probabilistic Modeling

Fall, 2011
M/W, 11:00AM - 12:20PM
Friend 004
David M. Blei
Piazza Site (discussion and announcements)


We will study some advanced methods in probabilistic modeling that are central to modern machine learning and statistics. We will focus on four subjects:

We will emphasize algorithms and applications as well as the theoretical underpinnings of these subjects.

Prerequisites and requirements

This course is appropriate for students who have taken COS513 "Foundations of Probabilistic Modeling" or who are familiar with the material from that course. Contact David Blei if you are unsure about whether this is the right course for you to take.

The course will consist of lectures and "practical" lectures. During practical lectures, we will implement and explore the properties of algorithms as a class. (We will learn and use R.)

The requirements are

Reading assignments


Introduction and review

Variational inference

Hierarchical modeling

Mixed-membership models

Bayesian nonparametrics

Scalable inference

Model assessment

R code