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• W2955316213 abstract "Precision matrix estimation is an important problem in statistical data analysis. This paper introduces a fast sparse precision matrix estimation algorithm, namely GISS$^{rho}$, which is originally introduced for compressive sensing. The algorithm GISS$^{rho}$ is derived based on $l_1$ minimization while with the computation advantage of greedy algorithms. We analyze the asymptotic convergence rate of the proposed GISS$^{rho}$ for sparse precision matrix estimation and sparsity recovery properties with respect to the stopping criteria. Finally, we numerically compare GISS$^{rho}$ to other sparse recovery algorithms, such as ADMM and HTP in three settings of precision matrix estimation. The numerical results show the advantages of the proposed algorithm." @default.
• W2955316213 created "2019-07-12" @default.
• W2955316213 creator A5052123856 @default.
• W2955316213 creator A5081667747 @default.
• W2955316213 date "2019-07-01" @default.
• W2955316213 modified "2023-09-27" @default.
• W2955316213 title "A greedy algorithm for sparse precision matrix approximation" @default.
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• W2955316213 hasPublicationYear "2019" @default.
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