An Expectation Conditional Maximization approach for Gaussian graphical models

20 September 2017

Papers citing "An Expectation Conditional Maximization approach for Gaussian graphical models"

9 / 9 papers shown

Title
The huge Package for High-dimensional Undirected Graph Estimation in R T. Zhao Han Liu Kathryn Roeder John D. Lafferty Larry A. Wasserman 34 480 0 26 Jun 2020
Scaling It Up: Stochastic Search Structure Learning in Graphical Models Hao Wang 280 116 0 07 May 2015
BDgraph: An R Package for Bayesian Structure Learning in Graphical Models Abdolreza Mohammadi E. Wit CML 44 102 0 21 Jan 2015
Regularized rank-based estimation of high-dimensional nonparanormal graphical models Lingzhou Xue H. Zou 81 263 0 13 Feb 2013
The Graphical Lasso: New Insights and Alternatives Rahul Mazumder Trevor Hastie 66 286 0 23 Nov 2011
Optimal rates of convergence for covariance matrix estimation Tommaso Cai Cun-Hui Zhang Harrison H. Zhou 85 474 0 19 Oct 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Han Liu Kathryn Roeder Larry A. Wasserman 62 484 0 16 Jun 2010
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs Han Liu John D. Lafferty Larry A. Wasserman 120 760 0 03 Mar 2009
Sparse permutation invariant covariance estimation Adam J. Rothman Peter J. Bickel Elizaveta Levina Ji Zhu 426 907 0 31 Jan 2008