Location: Haligan
Hall Ext.
Time: 9:30~10:30
l Zoubin Ghahramani, ICML
2004 tutorial: Tutorial
on Bayesian Machine Learning
l Zoubin Ghahramani,
UAI 2005 tutorial: Nonparametric
Bayesian Learning
l Yee Whye Teh, Machine
Learning Summer School 2007 Tutorial: Dirichlet
Process Tutorial and Practical Course.
l M. Jordan, NIPS
2005 tutorial: Nonparametric
Bayesian Methods: Dirichlet Processes, Chinese Restaurant Processes and All
That.
1.
Introduction to NP Bayesian and
GP (03/13/2009)
l D. J. C.
MacKay. Introduction
to Gaussian processes. In C. M. Bishop, editor, Neural Networks and Machine Learning,
volume 168 of NATO ASI
Series, pages 133-165. Springer, Berlin, 1998.
l C. K. I.
Williams. Prediction
with Gaussian processes: From linear regression to linear prediction and beyond.
In M. I. Jordan, editor, Learning
in Graphical Models, pages 599-621. The MIT Press, Cambridge, MA,
1999. Previously (1998)
1.
Gaussian Process for Machine
Learning (03/06/2009)
l M. Seeger.
Gaussian
processes for machine learning. International Journal of Neural
Systems, 14(2):69-106, 2004.
1.
Dirichlet Process Basics
(03/27/2009)
l Yee Whye Teh. Dirichlet
Process, Preprint.
l T. Ferguson. A
Bayesian analysis of some nonparametric problems. The Annals of Statistics,
1:209-230, 1973. [Optional]
2.
Dirichlet Process Mixture Model
(04/03/2009)
l Ananth Ranganathan. The Dirichlet Process Mixture (DPM) Model
l C. Antoniak. Mixtures
of Dirichlet processes with applications to Bayesian nonparametric problems. The
Annals of Statistics, 2(6):1152-1174, 1974. [Optional]
3.
Inference for Dirichlet Process
(04/10/2009)
l Neal, R.M.. Markov chain sampling methods for Dirichlet process mixture models. Journal of Computational and Graphical Statistics, 9, 249-265, 2000
l D. Blei, M. Jordan. Variational methods for Dirichlet Process. Proc. ICML, 2004
l D. Blei, M. Jordan. Variational inference for Dirichlet process mixtures. Journal of Bayesian Analysis, 1(1):121-144, 2005.[Optional]
4.
Hierarchical Dirichlet Process
with its application (04/17/2009)
l Y. Teh, M. Jordan, M. Beal, and D. Blei. Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101(476):1566-1581, 2007.
l Fox, E., Sudderth, E., Jordan, M., and Willsky, A. Developing a tempered HDP-HMM for systems with state persistence. Technical report, MIT Laboratory for Information and Decision Systems, 2007