High-dimensional Gaussian graphical model selection: walk summability and local separation criterion.
Animashree AnandkumarVincent Y. F. TanFurong HuangAlan S. WillskyPublished in: J. Mach. Learn. Res. (2012)
Keyphrases
- graphical models
- high dimensional
- belief propagation
- probabilistic model
- random variables
- probabilistic inference
- probabilistic graphical models
- approximate inference
- conditional random fields
- structure learning
- markov networks
- bayesian networks
- map inference
- low dimensional
- gaussian graphical models
- exact inference
- belief networks
- maximum likelihood
- nearest neighbor
- data points
- message passing
- graph structure
- graph cuts
- conditional independence
- dimensionality reduction
- undirected graphical models
- conditional dependencies
- similarity measure