Category Archives: Nonparametric Bayesian

HDP-LDA updates

Posted on August 15, 2012 by

Hierarchical Dirichlet Processes (Teh+ 2006) are a nonparametric bayesian topic model which can treat infinite topics. In particular, HDP-LDA is interesting as an extention of LDA. (Teh+ 2006) introduced updates of Collapsed Gibbs sampling for a general framework of HDP, … Continue reading →

Posted in LDA, Machine Learning, Nonparametric Bayesian | Leave a comment

[Kim+ ICML12] Dirichlet Process with Mixed Random Measures

Posted on July 31, 2012 by

We held a private reading meeting for ICML 2012. I took and introduced [Kim+ ICML12] “Dirichlet Process with Mixed Random Measures : A Nonparametric Topic Model for Labeled Data.” This is the presentation for it. DP-MRM [Kim+ ICML12] is a … Continue reading →

Posted in LDA, Machine Learning, Nonparametric Bayesian | 5 Comments