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 supervised topic model like sLDA [Blei+ 2007], DiscLDA [Lacoste-Julien+ 2008] and MedLDA [Zhu+ 2009], and is regarded as a nonparametric version of Labeled LDA [Ramage+ 2009] in particular.
Although Labeled LDA is easy to implement (my implementation is here), it has a disadvantage that you must specify label-topic correspondings explicitly and manually.
On the other hand, DP-MRM can automatically decide label-topic correspondings as distributions. I am very interested in it.
But it is hard to implement because it is a nonparametric bayesian modal.
Hence I don’t want infinite topics but hierarchical label-topic correspondings, I guess that it will become very useful and handy and fast to replace DPs into normal Dirichlet distributions in this model… I am going to try it! 😀