Stacked Graphical Models for Efficient Inference in Markov Random Fields.
Zhenzhen KouWilliam W. CohenPublished in: SDM (2007)
Keyphrases
- efficient inference
- graphical models
- markov random field
- probabilistic inference
- exact inference
- approximate inference
- belief propagation
- markov networks
- conditional random fields
- map inference
- factor graphs
- random variables
- probabilistic model
- probabilistic graphical models
- graph structure
- graph cuts
- message passing
- energy function
- bayesian networks
- higher order
- image segmentation
- energy minimization
- random fields
- structure learning
- belief networks
- loopy belief propagation
- maximum a posteriori
- influence diagrams
- parameter estimation
- undirected graphical models
- structured prediction
- pairwise
- potential functions
- conditional independence
- maximum margin
- machine learning
- upper bound