Streamlining Variational Inference for Constraint Satisfaction Problems.
Aditya GroverTudor AchimStefano ErmonPublished in: NeurIPS (2018)
Keyphrases
- constraint satisfaction problems
- variational inference
- bayesian inference
- topic models
- posterior distribution
- constraint satisfaction
- variational methods
- probabilistic model
- probabilistic graphical models
- gaussian process
- latent dirichlet allocation
- mixture model
- closed form
- constraint programming
- np complete
- search space
- graphical models
- exact inference
- non binary
- exponential family
- approximate inference
- np hard
- soft constraints
- factor graphs
- arc consistency
- hyperparameters
- bayesian networks
- level set
- generative model
- latent variables
- probability distribution
- bayesian framework
- prior information
- hidden variables
- belief propagation
- semi supervised
- first order logic