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ICML
2008
IEEE

The dynamic hierarchical Dirichlet process

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The dynamic hierarchical Dirichlet process
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are represented via a mixture associated with an appropriate underlying model, in the framework of HDP. The statistical properties of data collected at consecutive time points are linked via a random parameter that controls their probabilistic similarity. The sharing mechanisms of the timeevolving data are derived, and a relatively simple Markov Chain Monte Carlo sampler is developed. Experimental results are presented to demonstrate the model.
Lu Ren, David B. Dunson, Lawrence Carin
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2008
Where ICML
Authors Lu Ren, David B. Dunson, Lawrence Carin
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