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Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
A challenging problem in estimating high-dimensional graphical models is to choose the regularization parameter in a data-dependent way. The standard techniques include K-fold cross-validation (K-CV), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Though these methods...
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| Main Authors: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2010
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4138724/ https://ncbi.nlm.nih.gov/pubmed/25152607 |
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