The Hierarchical Dirichlet Process Hidden Semi-Markov Model
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode non-g...
Main Authors: | Johnson, Matthew James, Willsky, Alan S |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | en_US |
Published: |
Association for Uncertainty in Artificial Intelligence (AUAI)
2013
|
Online Access: | http://hdl.handle.net/1721.1/79638 https://orcid.org/0000-0003-0149-5888 |
Similar Items
-
Bayesian Nonparametric Hidden Semi-Markov Models
by: Johnson, Matthew James, et al.
Published: (2013) -
Multistate Diagnosis and Prognosis of Lubricating Oil Degradation Using Sticky Hierarchical Dirichlet Process–Hidden Markov Model Framework
by: Monika Tanwar, et al.
Published: (2021-07-01) -
Infinite hierarchical hidden Markov models
by: Heller, K, et al.
Published: (2009) -
Dirichlet forms and Markov processes /
by: 228719 Furushima, Masatoshi
Published: (1980) -
Hierarchical Dirichlet processes
by: Teh, Y, et al.
Published: (2006)