$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$

High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence

21 November 2008

Papers citing "High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence"

35 / 335 papers shown

Title
Gemini: Graph estimation with matrix variate normal instances Shuheng Zhou 66 105 0 23 Sep 2012
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains Majid Janzamin A. Anandkumar 21 3 0 27 Jun 2012
The Highest Dimensional Stochastic Blockmodel with a Regularized Estimator Karl Rohe Tai Qin Haoyang Fan 66 18 0 11 Jun 2012
Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection Shiqian Ma Lingzhou Xue H. Zou 47 101 0 06 Jun 2012
Estimating sufficient reductions of the predictors in abundant high-dimensional regressions R. Cook L. Forzani Adam J. Rothman 59 30 0 30 May 2012
Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization M. Slawski Matthias Hein 66 185 0 04 May 2012
Convergence Properties of Kronecker Graphical Lasso Algorithms Theodoros Tsiligkaridis Alfred Hero Shuheng Zhou 46 76 0 03 Apr 2012
Fast and Adaptive Sparse Precision Matrix Estimation in High Dimensions Weidong Liu Xi Luo 51 82 0 17 Mar 2012
Learning loopy graphical models with latent variables: Efficient methods and guarantees Anima Anandkumar R. Valluvan 47 50 0 17 Mar 2012
Learning High-Dimensional Mixtures of Graphical Models Anima Anandkumar Daniel J. Hsu F. Huang Sham Kakade 33 10 0 04 Mar 2012
Greedy Learning of Markov Network Structure Praneeth Netrapalli Siddhartha Banerjee Sujay Sanghavi Sanjay Shakkottai 52 56 0 08 Feb 2012
High-dimensional covariance matrix estimation with missing observations Karim Lounici 49 182 0 12 Jan 2012
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods Christopher C. Johnson A. Jalali Pradeep Ravikumar 31 59 0 29 Dec 2011
Bayesian model choice and information criteria in sparse generalized linear models Rina Foygel Mathias Drton 36 62 0 23 Dec 2011
Group Symmetry and Covariance Regularization P. Shah V. Chandrasekaran 50 27 0 30 Nov 2011
Learning a Factor Model via Regularized PCA Yi-Hao Kao Benjamin Van Roy 59 18 0 26 Nov 2011
A Direct Estimation Approach to Sparse Linear Discriminant Analysis Tony Cai Weidong Liu 36 280 0 18 Jul 2011
High-dimensional structure estimation in Ising models: Local separation criterion Anima Anandkumar Vincent Y. F. Tan Furong Huang A. Willsky 52 114 0 08 Jul 2011
High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion Anima Anandkumar Vincent Y. F. Tan A. Willsky 53 90 0 06 Jul 2011
Learning the Dependence Graph of Time Series with Latent Factors A. Jalali Sujay Sanghavi CML 54 44 0 09 Jun 2011
Lattices of Graphical Gaussian Models with Symmetries H. Gehrmann 53 12 0 08 Apr 2011
Estimating Networks With Jumps Mladen Kolar Eric P. Xing 67 66 0 17 Dec 2010
Extended Bayesian Information Criteria for Gaussian Graphical Models Rina Foygel Mathias Drton 36 853 0 30 Nov 2010
Optimal rates of convergence for covariance matrix estimation Tommaso Cai Cun-Hui Zhang Harrison H. Zhou 74 472 0 19 Oct 2010
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 73 1,369 0 13 Oct 2010
High-dimensional covariance estimation based on Gaussian graphical models Shuheng Zhou Philipp Rütimann Min Xu Peter Buhlmann 92 91 0 02 Sep 2010
Latent variable graphical model selection via convex optimization V. Chandrasekaran P. Parrilo A. Willsky CML 103 508 0 06 Aug 2010
Estimation of high-dimensional low-rank matrices Angelika Rohde Alexandre B. Tsybakov 98 378 0 29 Dec 2009
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity Sham Kakade Ohad Shamir Karthik Sindharan Ambuj Tewari 86 76 0 31 Oct 2009
Asymptotic distribution and sparsistency for l1-penalized parametric M-estimators with applications to linear SVM and logistic regression Guilherme V. Rocha Xing Wang Bin Yu 91 22 0 13 Aug 2009
Sparsistent Estimation of Time-Varying Discrete Markov Random Fields Mladen Kolar Eric P. Xing 99 23 0 14 Jul 2009
Information-theoretic limits of selecting binary graphical models in high dimensions N. Santhanam Martin J. Wainwright 71 203 0 16 May 2009
Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling Shuheng Zhou Sara van de Geer Peter Buhlmann 87 80 0 13 Mar 2009
Estimating time-varying networks Mladen Kolar Le Song Amr Ahmed Eric P. Xing AI4TS 83 309 0 30 Dec 2008
Time Varying Undirected Graphs Shuheng Zhou John D. Lafferty Larry A. Wasserman 116 240 0 20 Feb 2008