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The joint graphical lasso for inverse covariance estimation across multiple classes
We consider the problem of estimating multiple related Gaussian graphical models from a high-dimensional data set with observations belonging to distinct classes. We propose the joint graphical lasso, which borrows strength across the classes in order to estimate multiple graphical models that share...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2013
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4012833/ https://ncbi.nlm.nih.gov/pubmed/24817823 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/rssb.12033 |
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