Fast and Scalable Distributed Loopy Belief Propagation on Real-World Graphs.
Saehan JoJaemin YooU KangPublished in: WSDM (2018)
Keyphrases
- scalable distributed
- loopy belief propagation
- real world graphs
- connected components
- graph mining
- belief propagation
- community detection
- markov random field
- graphical models
- approximate inference
- power law
- power law distribution
- graph cuts
- real world
- free energy
- conditional random fields
- energy minimization
- file system
- binary images
- markov chain monte carlo
- higher order
- em algorithm
- message passing
- pattern mining
- community structure
- probabilistic inference
- stereo matching
- level set
- social networks
- latent variables
- image segmentation
- exact inference
- parameter estimation
- energy function
- gaussian process
- link analysis
- network analysis
- link prediction
- approximation algorithms