Estimation of sparse covariance matrix via non-convex regularization

Cites Work

Nearly unbiased variable selection under minimax concave penalty
Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data
One-step sparse estimates in nonconcave penalized likelihood models
Covariance regularization by thresholding
Operator norm consistent estimation of large-dimensional sparse covariance matrices
Sparse estimation of high-dimensional correlation matrices
Positive-definite modification of a covariance matrix by minimizing the matrix \(\ell_{\infty}\) norm with applications to portfolio optimization
Fixed support positive-definite modification of covariance matrix estimators via linear shrinkage
Multi-stage convex relaxation for feature selection
Adaptive robust variable selection
Positive definite estimators of large covariance matrices
Adaptive Thresholding for Sparse Covariance Matrix Estimation
Variational Analysis
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Positive-Definite ℓ₁-Penalized Estimation of Large Covariance Matrices
Generalized Thresholding of Large Covariance Matrices
Estimation of High Dimensional Mean Regression in the Absence of Symmetry and Light Tail Assumptions
Robust estimation of high-dimensional covariance and precision matrices
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Group Sparse Optimization for Images Recovery Using Capped Folded Concave Functions
Positive-definite thresholding estimators of covariance matrices with zeros
Robust covariance estimation for high-dimensional compositional data with application to microbial communities analysis
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)

This page was built for publication: Estimation of sparse covariance matrix via non-convex regularization

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6536688)