PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Note on the Implementation of Hierarchical Dirichlet Processes
Phil Blunsom, Trevor Cohn, Sharon Goldwater and Mark Johnson
In: ACL-IJCNLP 2009, 2-7 August 2009, Singapore.


The implementation of collapsed Gibbs samplers for non-parametric Bayesian models is non-trivial, requiring considerable book-keeping. Goldwater et al. (2006a) presented an approximation which significantly reduces the storage and computation overhead, but we show here that their formulation was incorrect and, even after correction, is grossly inaccurate. We present an alternative formulation which is exact and can be computed easily. However this approach does not work for hierarchical models, for which case we present an efficient data structure which has a better space complexity than the naive approach.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5884
Deposited By:Trevor Cohn
Deposited On:08 March 2010