Structure learning in graphical models by covariance queries.
Gábor LugosiJakub TruszkowskiVasiliki VelonaPiotr ZwiernikPublished in: CoRR (2019)
Keyphrases
- graphical models
- structure learning
- belief propagation
- probabilistic model
- bayesian networks
- approximate inference
- random variables
- probabilistic graphical models
- conditional independence
- probabilistic inference
- parameter learning
- markov networks
- markov logic networks
- conditional random fields
- dynamic bayesian networks
- belief networks
- exact inference
- factor graphs
- bayesian framework
- transfer learning
- feature selection