A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points.
Marco GrzegorczykPublished in: Mach. Learn. (2016)
Keyphrases
- hidden markov models
- dependency structure
- dynamic bayesian networks
- structure learning
- data points
- hidden states
- bayesian networks
- graphical models
- conditional random fields
- conditional independence
- parameter estimation
- high dimensional data
- semantic roles
- language model
- transfer learning
- particle filtering
- approximate inference
- unlabeled data
- sample size
- labeled data
- probabilistic model
- hidden variables
- network structure
- co occurrence
- probability distribution
- feature space