-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models?
Jiaxi YingJosé Vinícius de Miranda CardosoDaniel P. PalomarPublished in: CoRR (2020)
Keyphrases
- graphical models
- gaussian graphical models
- directed acyclic
- graph structure
- belief propagation
- probabilistic model
- probabilistic inference
- random variables
- probabilistic graphical models
- approximate inference
- structural learning
- markov networks
- structure learning
- conditional random fields
- conditional independence
- exact inference
- graphical structure
- map inference
- bayesian networks
- belief networks
- chain graphs
- undirected graphical models
- directed acyclic graph
- objective function
- directed graph
- sparse representation
- higher order
- possibilistic networks
- information extraction
- high dimensional