Nonparametric Bayesian methods (Dirichlet processes)
Lecturer: Kurt Miller
Date: Nov 19

[Lecture slides]


There are numerous references on Bayesian methods and Markov Chain Monte Carlo (MCMC) techniques. Three useful textbooks are:

Bayesian Data Analaysis. Gelman, Carlin, Stern, Rubin.
The Bayesian Choice. Robert.
Monte Carlo Statistical Methods. Robert, Casella.

Unfortunately, there currently are no good introductory textbooks on the Dirichlet Process. One of the best introductions to Dirichlet Processes is Chapter 2, Section 2.5 of Erik Sudderth's PhD thesis.

A great set of nonparametric Bayesian references can be found in the references section of a 2008 workshop on nonparametric Bayesian methods at ICML/UAI. This list includes many of the foundational papers about Dirichlet Processes as well as references to many recent applications.

Tutorials on nonparametric Bayesian methods