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On the inconsistency of ℓ(1)-penalised sparse precision matrix estimation
BACKGROUND: Various ℓ (1)-penalised estimation methods such as graphical lasso and CLIME are widely used for sparse precision matrix estimation and learning of undirected network structure from data. Many of these methods have been shown to be consistent under various quantitative assumptions about...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249033/ https://www.ncbi.nlm.nih.gov/pubmed/28105909 http://dx.doi.org/10.1186/s12859-016-1309-x |