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The cluster graphical lasso for improved estimation of Gaussian graphical models

The task of estimating a Gaussian graphical model in the high-dimensional setting is considered. The graphical lasso, which involves maximizing the Gaussian log likelihood subject to a lasso penalty, is a well-studied approach for this task. A surprising connection between the graphical lasso and hi...

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Detalles Bibliográficos
Publicado en:Comput Stat Data Anal
Autores principales: Tan, Kean Ming, Witten, Daniela, Shojaie, Ali
Formato: Artigo
Lenguaje:Inglês
Publicado: 2014
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Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC4307846/
https://ncbi.nlm.nih.gov/pubmed/25642008
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csda.2014.11.015
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