Approximate Inference Using DC Programming For Collective Graphical Models.
Duc Thien NguyenAkshat KumarHoong Chuin LauDaniel SheldonPublished in: AISTATS (2016)
Keyphrases
- approximate inference
- graphical models
- belief propagation
- probabilistic inference
- probabilistic model
- exact inference
- random variables
- probabilistic graphical models
- structure learning
- variational methods
- loopy belief propagation
- factor graphs
- markov networks
- dynamic bayesian networks
- partition function
- bayesian networks
- conditional random fields
- generalized belief propagation
- conditional independence
- message passing
- free energy
- structured prediction
- cutting plane
- latent variables
- convex functions
- belief networks
- prior information
- undirected graphical models
- image segmentation