An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation

DOI10.1016/j.csda.2018.07.011zbMath1469.62106OpenAlexW2882971772WikidataQ129459766 ScholiaQ129459766MaRDI QIDQ1796959

Peili Li, Yun-hai Xiao

Publication date: 17 October 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.07.011

zbMATH Keywords

alternating direction method of multipliersnon-smooth convex minimizationLagrangian dualinverse covariance matrixsymmetric Gauss-Seidel iteration

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12)

Related Items (5)

Sparse recovery via nonconvex regularized \(M\)-estimators over \(\ell_q\)-balls ⋮ Efficient dual ADMMs for sparse compressive sensing MRI reconstruction ⋮ An extended linearized alternating direction method of multipliers for fused-Lasso penalized linear regression ⋮ A dual spectral projected gradient method for log-determinant semidefinite problems ⋮ Sparse estimation of high-dimensional inverse covariance matrices with explicit eigenvalue constraints

Uses Software

• glasso
• MIM
• HdBCS

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