Maximum A Posteriori Approximation of Dirichlet and Beta-Liouville Hidden Markov Models for Proportional Sequential Data Modeling.
Samr AliNizar BouguilaPublished in: SMC (2020)
Keyphrases
- sequential data
- hidden markov models
- maximum a posteriori
- em algorithm
- markov random field
- expectation maximization
- maximum likelihood
- image reconstruction
- bayesian framework
- hyperparameters
- markov models
- energy function
- baum welch
- mixture model
- conditional random fields
- prior distribution
- hidden states
- pattern discovery
- posterior distribution
- fixed length
- sequential pattern mining
- sequential patterns
- graph cuts
- feature vectors
- pattern mining
- reinforcement learning
- closed form
- probabilistic model
- sequence classification
- spatio temporal