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Applications on inference of biological networks have raised a strong interest in the problem of graph estimation in high-dimensional Gaussian graphical models.
Correspondence analysis of genes and tissue types and finding genetic links from microarray data
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Adaptive estimation of a quadratic functional by model selection
B. Laurent and P. Massart · 2000
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P. Spirtes, C. Glymour, and R. Scheines · 2000
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L. Birgé and P. Massart · 2001
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Adaptive tests of linear hypotheses by model selection
Y. Baraud, S. Huet, and B. Laurent · 2003
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Bayesian inference for nondecomposable graphical Gaussian models
P. Dellaportas, P. Giudici, and G. Roberts · 2003
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Efficient estimation of covariance selection models
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Sparse graphical models for exploring gene expression data
A. Dobra, C. Hans, B. Jones, J. Nevins, G. Yao, and M. West · 2004
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B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani · 2004
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A robust procedure for Gaussian graphical model search from microarray data with p p larger than n n
R. Castelo and A. Roverato · 2006
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Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer
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Covariance matrix selection and estimation via penalised normal likelihood
J. Huang, N. Liu, M. Pourahmadi, and L. Liu · 2006
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High-dimensional graphs and variable selection with the lasso
N. Meinshausen and P. Bühlmann · 2006
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Low-order conditional independence graphs for inferring genetic networks
A. Wille and P. Bühlmann · 2006
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Exploring gene causal interactions using an enhanced constraint-based method
W. Wu and Y. Ye · 2006
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The adaptive lasso and its oracle properties
H. Zou · 2006
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Model selection and estimation in the Gaussian graphical model
M. Yuan and Y. Lin · 2007
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Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data
O. Banerjee, L. El Ghaoui, and A. d’Aspremont · 2008
A path following algorithm for sparse pseudo-likelihood inverse covariance estimation (splice)
G. Rocha, P. Zhao, and B. Yu · 2008
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Sparse permutation invariant covariance estimation
A. Rothman, P. Bickel, E. Levina, and J. Zhu · 2008
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Inferring sparse Gaussian graphical models with latent structure
Christophe Ambroise, Julien Chiquet, and Catherine Matias · 2009
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Gaussian model selection with an unknown variance
Y. Baraud, C. Giraud, and S. Huet · 2009
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SIMoNe: Statistical Inference for MOdular NEtworks
Julien Chiquet, Alexander Smith, Gilles Grasseau, Catherine Matias, and Christophe Ambroise · 2009
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Sparse regression learning by aggregation and langevin monte-carlo, 2009
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Aggregation by exponential weighting, sharp oracle inequalities and sparsity
A. Dalayan and A. Tsybakov · 2008
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Sparse inverse covariance estimation with the lasso
J. Friedman, T. Hastie, and R. Tibshirani · 2008
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Estimation of Gaussian graphs by model selection
C. Giraud · 2008
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Robustification of the pc-algorithm for directed acyclic graphs
M. Kalisch and P. Bühlmann · 2008
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Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both complete and incomplete responses
Rene Natowicz, Roberto Incitti, Euler Guimaraes Horta, Benoit Charles, Philippe Guinot, Kai Yan, Charles Coutant, Fabrice Andre, Lajos Pusztai, and Roman Rouzier · 2008
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A. Dalayan and A. Tsybakov · 2009
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Network exploration via the adaptive lasso and scad penalties
J. Fan, Y. Feng, and Y. Wu · 2009
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Sparsistency and Rates of Convergence in Large Covariance Matrices Estimation
C. Lam and J. Fan · 2009
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Feature-inclusion stochastic search for gaussian graphical models
J.G. Scott and C. M. Carvalho · 2009
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High-dimensional gaussian model selection on a gaussian design
N. Verzelen · 2010
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Minimax risks for sparse regressions: Ultra-high-dimensional phenomenons., 2010
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