$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
Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity Andersen Chang Lili Zheng Genevera I. Allen 13 3 0 17 Sep 2022
On the Lasso for Graphical Continuous Lyapunov Models Philipp Dettling Mathias Drton Mladen Kolar 6 6 0 29 Aug 2022
On confidence intervals for precision matrices and the eigendecomposition of covariance matrices Teodora Popordanoska A. Tiulpin Wacha Bounliphone Matthew B. Blaschko 11 0 0 25 Aug 2022
Learning the Structure of Large Networked Systems Obeying Conservation Laws Anirudh Rayas A. Rajasekhar Gautam Dasarathy 13 5 0 14 Jun 2022
Supervised Dictionary Learning with Auxiliary Covariates Joo-Hyun Lee Hanbaek Lyu W. Yao 27 1 0 14 Jun 2022
Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patterns Chuyang Ke Jean Honorio 15 0 0 10 Jun 2022
Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation Adarsh Barik Jean Honorio 11 6 0 02 Jun 2022
uGLAD: Sparse graph recovery by optimizing deep unrolled networks H. Shrivastava Urszula Chajewska Robin Abraham Xinshi Chen 39 8 0 23 May 2022
Structure Learning in Graphical Models from Indirect Observations Hang Zhang Afshin Abdi Faramarz Fekri CML 24 0 0 06 May 2022
Order-based Structure Learning without Score Equivalence Hyunwoong Chang James Cai Quan Zhou CML OffRL 29 3 0 10 Feb 2022
Total positivity in multivariate extremes Frank Rottger Sebastian Engelke Piotr Zwiernik 39 20 0 29 Dec 2021
An additive graphical model for discrete data Jun Tao Bing Li Lingzhou Xue 8 3 0 29 Dec 2021
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity Jian-Feng Cai José Vinícius de Miranda Cardoso Daniel P. Palomar Jiaxi Ying 35 10 0 03 Dec 2021
Optimal regularizations for data generation with probabilistic graphical models Arnaud Fanthomme Francesca Rizzato Simona Cocco R. Monasson 9 3 0 02 Dec 2021
Sparse Graph Learning Under Laplacian-Related Constraints Jitendra Tugnait 17 12 0 16 Nov 2021
On Sparse High-Dimensional Graphical Model Learning For Dependent Time Series Jitendra Tugnait CML 23 13 0 15 Nov 2021
Scalable Intervention Target Estimation in Linear Models Burak Varici Karthikeyan Shanmugam P. Sattigeri A. Tajer CML 17 9 0 15 Nov 2021
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... C. Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 38 50 0 09 Nov 2021
Learning linear non-Gaussian directed acyclic graph with diverging number of nodes Ruixuan Zhao Xin He Junhui Wang CML 37 5 0 01 Nov 2021
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles Tianyi Yao Minjie Wang Genevera I. Allen 11 0 0 22 Oct 2021
On Optimal Interpolation In Linear Regression Eduard Oravkin Patrick Rebeschini 11 3 0 21 Oct 2021
Joint Functional Gaussian Graphical Models Ilias Moysidis Bing Li 27 3 0 13 Oct 2021
Estimation When Both Covariance And Precision Matrices Are Sparse S. MacNamara Erik Schlögl Z. Botev 14 1 0 15 Aug 2021
The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property Iain Carmichael 32 2 0 07 Jul 2021
A unified precision matrix estimation framework via sparse column-wise inverse operator under weak sparsity Zeyu Wu Cheng-Long Wang Weidong Liu 36 3 0 07 Jul 2021
MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation Qian Li Binyan Jiang Defeng Sun 11 3 0 25 Jun 2021
A Bayesian approach for partial Gaussian graphical models with sparsity Eunice Okome Obiang Pascal Jézéquel Frédéric Proia 6 1 0 23 May 2021
Definite Non-Ancestral Relations and Structure Learning Wenyu Chen Mathias Drton Ali Shojaie CML 12 1 0 20 May 2021
Learning Gaussian Graphical Models with Latent Confounders Ke Wang Alexander M. Franks Sang-Yun Oh CML 29 2 0 14 May 2021
Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity Minjie Wang Genevera I. Allen 11 5 0 13 Apr 2021
Nonparametric and high-dimensional functional graphical models Eftychia Solea Holger Dette 44 14 0 18 Mar 2021
$Asymptotic Theory of $\ell_1$-Regularized PDE Identification from a Single Noisy Trajectory$ Asymptotic Theory of $\ell_1$ -Regularized PDE Identification from a Single Noisy Trajectory Yuchen He Namjoon Suh X. Huo Sungha Kang Y. Mei 21 1 0 12 Mar 2021
Joint Network Topology Inference via Structured Fusion Regularization Yanli Yuan D. Soh Xiao Yang Kun Guo Tony Q. S. Quek 29 2 0 05 Mar 2021
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation Mayee F. Chen Benjamin Cohen-Wang Stephen Mussmann Frederic Sala Christopher Ré 43 10 0 03 Mar 2021
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem Adarsh Barik Jean Honorio FaML 19 7 0 19 Feb 2021
Scalable Inference of Sparsely-changing Markov Random Fields with Strong Statistical Guarantees S. Fattahi A. Gómez 21 5 0 06 Feb 2021
Tree-based Node Aggregation in Sparse Graphical Models Ines Wilms Jacob Bien 18 4 0 29 Jan 2021
Graphical Elastic Net and Target Matrices: Fast Algorithms and Software for Sparse Precision Matrix Estimation Solt Kovács Tobias Ruckstuhl Helena Obrist Peter Buhlmann 24 9 0 06 Jan 2021
Estimation of Shortest Path Covariance Matrices R. Maity Cameron Musco 12 0 0 19 Nov 2020
FiGLearn: Filter and Graph Learning using Optimal Transport Matthias Minder Zahra Farsijani Dhruti Shah Mireille El Gheche P. Frossard OT 8 1 0 29 Oct 2020
On Learning Continuous Pairwise Markov Random Fields Abhin Shah Devavrat Shah G. Wornell 11 11 0 28 Oct 2020
Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control Sai Li T. Tony Cai Hongzhe Li 22 52 0 21 Oct 2020
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent Matthew Brennan Guy Bresler Samuel B. Hopkins J. Li T. Schramm 19 62 0 13 Sep 2020
Covariance estimation with nonnegative partial correlations Jake A. Soloff Adityanand Guntuboyina Michael I. Jordan 15 10 0 30 Jul 2020
A General Family of Stochastic Proximal Gradient Methods for Deep Learning Jihun Yun A. Lozano Eunho Yang 20 12 0 15 Jul 2020
Asymptotic control of FWER under Gaussian assumption: application to correlation tests S. Achard Pierre Borgnat Irène Gannaz 11 1 0 02 Jul 2020
Testing and Support Recovery of Correlation Structures for Matrix-Valued Observations with an Application to Stock Market Data Xin Chen Dan Yang Yan Xu Yin Xia Dong Wang Haipeng Shen 31 9 0 30 Jun 2020
$Does the $\ell_1$-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models?$ Does the $\ell_1$ -norm Learn a Sparse Graph under Laplacian Constrained Graphical Models? Jiaxi Ying J. Cardoso Daniel P. Palomar 8 10 0 26 Jun 2020
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation Qian Zhang Yilin Zheng Jean Honorio 60 6 0 22 Jun 2020
Exact Support Recovery in Federated Regression with One-shot Communication Adarsh Barik Jean Honorio FedML 43 2 0 22 Jun 2020