The Infinite Hidden Markov Model

@inproceedings{Beal2001TheIH,
  title={The Infinite Hidden Markov Model},
  author={Matthew J. Beal and Zoubin Ghahramani and C. Rasmussen},
  booktitle={NIPS},
  year={2001}
}
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integrate out the infinitely many transition parameters, leaving only three hyperparameters which can be learned from data. These three hyperparameters define a hierarchical Dirichlet process capable of capturing a rich set of transition dynamics. The three hyperparameters control the time scale of the dynamics, the… Expand
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