Exploiting sparse markov and covariance structure in multiresolution models

Exploiting sparse markov and covariance structure in multiresolution models

We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR models have limited modeling capabilities, as variables at one scale are forced to be uncorrelated with each other condit...

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Bibliographic Details
Main Authors: Choi, Myung Jin (Contributor), Chandrasekaran, Venkat (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: Association for Computing Machinery / ACM Digital Library, 2011-09-21T17:51:36Z.
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