Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models.

Junwei Lu Mladen Kolar Han Liu

Published in: J. Mach. Learn. Res. (2017)

Keyphrases

graphical models
probabilistic inference
exact inference
map inference
belief networks
bayesian networks
belief propagation
factor graphs
approximate inference
undirected graphical models

loopy belief propagation
nonparametric belief propagation
efficient inference algorithms
probabilistic model
random variables
probabilistic graphical models
statistical inference
structure learning
conditional random fields
directed graphical models

markov networks
collective classification
markov logic networks
relational dependency networks
possibilistic networks
statistical relational learning
probabilistic networks
dynamic bayesian networks
graphical structure

probabilistic reasoning
structured prediction
chain graphs
bayesian inference
message passing
junction tree
image labeling
latent variables
lower bound