Recursive FMP for distributed inference in Gaussian graphical models

Recursive FMP for distributed inference in Gaussian graphical models

For inference in Gaussian graphical models with cycles, loopy belief propagation (LBP) performs well for some graphs, but often diverges or has slow convergence. When LBP does converge, the variance estimates are incorrect in general. The feedback message passing (FMP) algorithm has been proposed to...

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Bibliographic Details
Main Authors: Liu, Ying (Contributor), Willsky, Alan S. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-10-21T15:24:40Z.
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