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A single, stationary topic model such as la-tent Dirichlet allocation is inappropriate for modeling corpora that span long time peri-ods, as the popularity of topics is likely to change over time. A n...
The inferential problem of associating data to mixture components is dif- ficult when components are nearby or overlapping. We introduce a new split-merge Markov chain Monte Carlo technique that eff...
In this paper we propose a generalised iterative algorithm for calcu- lating variational Bayesian estimates for a normal mixture model and investigate its convergence properties. It is shown theoret...
We present a systematic study of several recently proposed methods of mean field inference for the Dirichlet process mixture (DPM) model. These methods provide approximations to the posterior distribu...
This paper proposes a new method to combine several densities such that each density dominates a separate part of a joint distribution. The method is fully unsupervised, i.e. the parameters in the d...

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