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Annals of Statistics

Volumn 40, Issue 4, 2012, Pages 1984-1988

Discussion: Latent variable graphical model selection via convex optimization

(2) Giraud, Christophe a Tsybakov, Alexandre b

a CENTRE DE MATHÉMATIQUES APPLIQUÉES (France)

b Crest Ensae (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84872003285 PISSN: 00905364 EISSN: None Source Type: Journal
DOI: 10.1214/12-AOS984 Document Type: Note

Times cited : (14)

References (9)

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2
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- Sparse inverse covariance estimation with the graphical Lasso
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3
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- Estimation of Gaussian graphs by model selection
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- Giraud, C.¹

4
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- Graph selection with GGMselect
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5
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- Available at arXiv:1201.2577
- LOUNICI, K. (2012). High-dimensional covariance matrix estimation with missing observations. Available at arXiv:1201.2577.
- (2012) High-dimensional Covariance Matrix Estimation with Missing Observations
- Lounici, K.¹

6
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- High-dimensional graphs and variable selection with the lasso
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- (2006) Ann Statist. , vol.34 , pp. 1436-1462
- Meinshausen, N.¹ Bühlmann, P.²

7
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- High-dimensional covariance estimation by minimizingτ1-penalized log-determinant divergence
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- RAVIKUMAR, P.,WAINWRIGHT, M. J., RASKUTTI, G. andYU, B. (2011). High-dimensional covariance estimation by minimizingτ1-penalized log-determinant divergence. Electron. J. Stat. 5 935-980. MR2836766
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8
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- Available at arXiv:1202.2723
- SUN, T. and ZHANG, C. H. (2012). Sparse matrix inversion with scaled lasso. Available at arXiv:1202.2723.
- (2012) Sparse Matrix Inversion with Scaled Lasso
- Sun, T.¹ Zhang, C.H.²

9
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- Assessing the validity domains of graphical Gaussian models in order to infer relationships among components of complex biological systems
- Art. 14 MR2465331
- VILLERS, F., SCHAEFFER, B., BERTIN, C. and HUET, S. (2008). Assessing the validity domains of graphical Gaussian models in order to infer relationships among components of complex biological systems. Stat. Appl. Genet. Mol. Biol. 7 Art. 14, 36. MR2465331
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