Hamming ball auxiliary sampling for factorial hidden Markov models
We introduce a novel sampling algorithm for Markov chain Monte Carlo-based Bayesian inference for factorial hidden Markov models. This algorithm is based on an auxiliary variable construction that restricts the model space allowing iterative exploration in polynomial time. The sampling approach over...
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| Format: | Conference item |
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Curran Associates, Inc.
2014
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