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» Beam sampling for the infinite hidden Markov model
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ICML
2008
IEEE
14 years 4 months ago
Beam sampling for the infinite hidden Markov model
The infinite hidden Markov model is a nonparametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov...
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubi...
NIPS
2008
13 years 5 months ago
The Infinite Factorial Hidden Markov Model
We introduce a new probability distribution over a potentially infinite number of binary Markov chains which we call the Markov Indian buffet process. This process extends the IBP...
Jurgen Van Gael, Yee Whye Teh, Zoubin Ghahramani
CORR
2012
Springer
210views Education» more  CORR 2012»
11 years 11 months ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
NIPS
2001
13 years 5 months ago
The Infinite Hidden Markov Model
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 integ...
Matthew J. Beal, Zoubin Ghahramani, Carl Edward Ra...
ECML
2005
Springer
13 years 9 months ago
Inducing Hidden Markov Models to Model Long-Term Dependencies
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Jérôme Callut, Pierre Dupont