$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"

50 / 335 papers shown

Title
Sparse and compositionally robust inference of microbial ecological networks Zachary D. Kurtz Christian L. Müller Emily R. Miraldi D. Littman M. Blaser Richard Bonneau 34 1,224 0 18 Aug 2014
Sure Screening for Gaussian Graphical Models Shuang Luo R. Song Daniela Witten 29 22 0 29 Jul 2014
Learning Latent Variable Gaussian Graphical Models Zhaoshi Meng Brian Eriksson Alfred Hero 22 41 0 10 Jun 2014
Convex Banding of the Covariance Matrix Jacob Bien F. Bunea Luo Xiao 30 44 0 23 May 2014
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach S. Tajbakhsh N. Aybat E. Castillo 41 10 0 21 May 2014
High Dimensional Semiparametric Latent Graphical Model for Mixed Data Jianqing Fan Han Liu Y. Ning H. Zou 39 120 0 29 Apr 2014
Estimation of positive definite M-matrices and structure learning for attractive Gaussian Markov Random fields M. Slawski Matthias Hein 43 104 0 26 Apr 2014
A Note on Moment Inequality for Quadratic Forms Xiaohui Chen 42 3 0 04 Apr 2014
Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach A. Jung 37 31 0 04 Apr 2014
Worst possible sub-directions in high-dimensional models Sara van de Geer 43 11 0 27 Mar 2014
Confidence intervals for high-dimensional inverse covariance estimation Jana Janková Sara van de Geer 66 185 0 26 Mar 2014
Statistical Structure Learning, Towards a Robust Smart Grid Hanie Sedghi E. Jonckheere 141 4 0 07 Mar 2014
Learning Graphical Models With Hubs Kean Ming Tan Palma London Karthika Mohan Su-In Lee Maryam Fazel Daniela Witten 38 98 0 28 Feb 2014
Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Noisy Matrix Decomposition Hanie Sedghi Anima Anandkumar E. Jonckheere 48 13 0 20 Feb 2014
Sparsistency and agnostic inference in sparse PCA Jing Lei Vincent Q. Vu 36 54 0 27 Jan 2014
Performance Analysis of Tyler's Covariance Estimator I. Soloveychik A. Wiesel 31 22 0 27 Jan 2014
Covariance and precision matrix estimation for high-dimensional time series Xiaohui Chen Mengyu Xu Wei Biao Wu AI4TS 70 146 0 06 Jan 2014
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks Bryon Aragam Qing Zhou CML 57 107 0 04 Jan 2014
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint Ji Liu R. Fujimaki Jieping Ye 38 45 0 31 Dec 2013
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization Xiao-Tong Yuan Ping Li Tong Zhang 44 113 0 22 Nov 2013
Learning Pairwise Graphical Models with Nonlinear Sufficient Statistics Xiao-Tong Yuan Ping Li Tong Zhang 38 1 0 21 Nov 2013
High-dimensional learning of linear causal networks via inverse covariance estimation Po-Ling Loh Peter Buhlmann CML 59 189 0 14 Nov 2013
An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization Quoc Tran-Dinh Anastasios Kyrillidis V. Cevher 19 29 0 07 Nov 2013
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models Jean Honorio Tommi Jaakkola 37 25 0 26 Sep 2013
Asymptotic normality and optimalities in estimation of large Gaussian graphical models Zhao Ren Tingni Sun Cun-Hui Zhang Harrison H. Zhou 66 244 0 24 Sep 2013
Composite Self-Concordant Minimization Quoc Tran-Dinh Anastasios Kyrillidis V. Cevher 41 94 0 13 Aug 2013
The Cluster Graphical Lasso for improved estimation of Gaussian graphical models Kean Ming Tan Daniela Witten Ali Shojaie 70 71 0 19 Jul 2013
A Survey on Metric Learning for Feature Vectors and Structured Data A. Bellet Amaury Habrard M. Sebban 53 680 0 28 Jun 2013
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation Cho-Jui Hsieh Mátyás A. Sustik Inderjit S. Dhillon Pradeep Ravikumar 26 343 0 13 Jun 2013
On model selection consistency of regularized M-estimators J. Lee Yuekai Sun Jonathan E. Taylor 42 45 0 31 May 2013
Regularity Properties for Sparse Regression Yan Sun Jianqing Fan 35 9 0 22 May 2013
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices Tony Cai Zongming Ma Yihong Wu 37 159 0 14 May 2013
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima Po-Ling Loh Martin J. Wainwright 31 512 0 10 May 2013
A Junction Tree Framework for Undirected Graphical Model Selection Divyanshu Vats Robert D. Nowak CML 51 8 0 17 Apr 2013
Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models Zhaoshi Meng Dennis L. Wei A. Wiesel Alfred Hero 28 25 0 19 Mar 2013
Regularized rank-based estimation of high-dimensional nonparanormal graphical models Lingzhou Xue H. Zou 37 263 0 13 Feb 2013
Optimal rates of convergence for sparse covariance matrix estimation T. Cai Harrison H. Zhou 96 245 0 13 Feb 2013
Covariance Estimation in High Dimensions via Kronecker Product Expansions Theodoros Tsiligkaridis Alfred Hero 33 110 0 12 Feb 2013
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions Quoc Tran-Dinh Anastasios Kyrillidis V. Cevher 33 29 0 08 Jan 2013
Optimal classification in sparse Gaussian graphic model Yingying Fan Jiashun Jin Zhigang Yao 36 38 0 21 Dec 2012
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses Po-Ling Loh Martin J. Wainwright 37 180 0 03 Dec 2012
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models Majid Janzamin Anima Anandkumar 33 12 0 05 Nov 2012
Discussion: Latent variable graphical model selection via convex optimization Emmanuel J. Candés Mahdi Soltanolkotabi 44 39 0 05 Nov 2012
Discussion: Latent variable graphical model selection via convex optimization Zhao Ren Harrison H. Zhou 30 3 0 05 Nov 2012
Discussion: Latent variable graphical model selection via convex optimization Christophe Giraud Alexandre B. Tsybakov 28 8 0 05 Nov 2012
Discussion: Latent variable graphical model selection via convex optimization Martin J. Wainwright 40 8 0 05 Nov 2012
Adaptive covariance matrix estimation through block thresholding By T. Tony Cai M. Yuan 32 129 0 02 Nov 2012
Parallel MCMC with Generalized Elliptical Slice Sampling Robert Nishihara Iain Murray Ryan P. Adams 62 79 0 28 Oct 2012
Strong oracle optimality of folded concave penalized estimation Jianqing Fan Lingzhou Xue H. Zou 54 302 0 22 Oct 2012
Partial Gaussian Graphical Model Estimation Xiao-Tong Yuan Tong Zhang 47 42 0 28 Sep 2012