A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data
type: Item
instance of: scholarly article
title: A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data
zbMATH Open document ID: 1447.62048
author: Yanyan Li
published in: Machine Learning
publication date: 2019-11-26T00:00:00Z
Mathematics Subject Classification ID: 62G30
Mathematics Subject Classification ID: 62J10
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7136680
zbMATH Keywords: covariance estimation
zbMATH Keywords: high-dimensional data
zbMATH Keywords: sparse Cholesky
zbMATH Keywords: penalized likelihood
describes a project that uses: glasso
describes a project that uses: glmnet
MaRDI profile type: Publication
full work available at URL: s10994-019-05810-5
OpenAlex ID: W2948834710
cites work: Q5744839
cites work: Q3096116
cites work: A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
cites work: Sparse inverse covariance estimation with the graphical lasso
cites work: Q2934102
cites work: Covariance matrix selection and estimation via penalised normal likelihood
cites work: A Convex Pseudolikelihood Framework for High Dimensional Partial Correlation Estimation with Convergence Guarantees
cites work: Estimation of high-dimensional graphical models using regularized score matching
cites work: Fast and adaptive sparse precision matrix estimation in high dimensions
cites work: Q5405145
cites work: High-dimensional graphs and variable selection with the Lasso
cites work: Schur products and matrix completions
cites work: Partial Correlation Estimation by Joint Sparse Regression Models
cites work: A new approach to Cholesky-based covariance regularization in high dimensions
cites work: Analysis of call centre arrival data using singular value decomposition
cites work: Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
cites work: Parsimonious Covariance Matrix Estimation for Longitudinal Data
cites work: \(\ell_{0}\)-penalized maximum likelihood for sparse directed acyclic graphs
cites work: Nonparametric estimation of large covariance matrices of longitudinal data
cites work: Learning Local Dependence In Ordered Data
cites work: High dimensional inverse covariance matrix estimation via linear programming
cites work: Sparse precision matrix estimation via lasso penalized D-trace loss
cites work: Cholesky-based model averaging for covariance matrix estimation
Wikidata QID: Q127755425
DOI: 10.1007/S10994-019-05810-5
description: scientific article; zbMATH DE number 7136680