Right now, probably the best general purpose methods for what Frank Wood and Yee Whye Teh called the Graphical Pitman-Yor Process (see their AI&Stats 2009 paper) are ours using table indicators. I gave a tutorial on the hierarchical Dirichlet Process, and the hierarchical Pitman-Yor Process at Monash last week, and the slides are here. Still developing these, so they will be improved. Haven’t made the extension from hierarchical to graphical yet but its in Lan Du‘s PhD thesis. The examples given in the tutorial are about topic models and n-gram models.
Archive for October, 2014
Talk at RMIT on “Latent Semantic Modelling”
October 16, 2014I realised non-parametric methods are rather like deep neural networks. Anyway, here’s a more high level talk given at RMIT summarising recent work.
Bayesian Models 