Sampling from Gaussian graphical models using subgraph perturbations
The problem of efficiently drawing samples from a Gaussian graphical model or Gaussian Markov random field is studied. We introduce the subgraph perturbation sampling algorithm, which makes use of any pre-existing tractable inference algorithm for a subgraph by perturbing this algorithm so as to yie...
Main Authors: | Liu, Ying (Contributor), Kosut, Oliver (Author), Willsky, Alan S. (Contributor) |
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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),
2014-10-21T17:02:47Z.
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Subjects: | |
Online Access: | Get fulltext |
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