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Tensor graphical lasso (TeraLasso)
dc.contributor.authorGreenewald, Kristjan
dc.contributor.authorZhou, Shuheng
dc.contributor.authorHero, Alfred
dc.date.accessioned2019-11-12T16:22:49Z
dc.date.availableWITHHELD_13_MONTHS
dc.date.available2019-11-12T16:22:49Z
dc.date.issued2019-11
dc.identifier.citationGreenewald, Kristjan; Zhou, Shuheng; Hero, Alfred (2019). "Tensor graphical lasso (TeraLasso)." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 81(5): 901-931.
dc.identifier.issn1369-7412
dc.identifier.issn1467-9868
dc.identifier.urihttps://hdl.handle.net/2027.42/152015
dc.publisherCambridge University Press
dc.publisherWiley Periodicals, Inc.
dc.subject.otherNon‐separable factor models
dc.subject.otherPrecision matrix estimation
dc.subject.otherSparsity
dc.subject.otherKronecker sum
dc.subject.otherCovariance modelling for array‐valued data
dc.subject.otherConvergence guarantees
dc.titleTensor graphical lasso (TeraLasso)
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152015/1/rssb12339_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152015/2/rssb12339.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152015/3/rssb12339-sup-0001-Supinfo.pdf
dc.identifier.doi10.1111/rssb.12339
dc.identifier.sourceJournal of the Royal Statistical Society: Series B (Statistical Methodology)
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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