Message Passing for Collective Graphical Models.
Tao SunDaniel SheldonAkshat KumarPublished in: ICML (2015)
Keyphrases
- message passing
- graphical models
- belief propagation
- approximate inference
- probabilistic inference
- factor graphs
- probabilistic model
- random variables
- probabilistic graphical models
- markov networks
- bayesian networks
- conditional random fields
- loopy belief propagation
- energy minimization
- exact inference
- structure learning
- conditional independence
- free energy
- belief networks
- map inference
- influence diagrams
- reinforcement learning
- partition function
- graph cuts
- clique potentials
- distributed systems
- linear programming
- high quality
- generalized belief propagation