High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood.
Kimmo SuotsaloYingying XuJukka CoranderJohan PensarPublished in: Stat. Comput. (2021)
Keyphrases
- structure learning
- high dimensional
- autoregressive model
- markov logic networks
- markov networks
- graphical models
- markov blanket
- probabilistic graphical models
- bayesian networks
- parameter learning
- conditional independence
- bayesian network classifiers
- maximum likelihood
- belief propagation
- parameter estimation
- transfer learning
- first order logic
- feature space
- probability distribution
- variable selection
- data points
- random variables
- high dimensional data
- conditional random fields
- exact inference
- approximate inference
- computer vision
- probabilistic model
- feature vectors
- markov random field
- random fields
- probabilistic inference
- posterior probability
- sample size
- hidden variables
- bayesian inference