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Enhancing sparsity by reweighted l1 minimization
1-Minimization ·Iterative reweighting Underdetermined systems of linear equations·Compressive sensing Dantzig selector· Sparsity FOCUSS
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2015/8/10
It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by constraine...
A differential equations approach to l1-minimization with applications to array imaging
differential equations approach l1-minimization array imaging
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2015/7/14
We present an ordinary differential equations approach to the analysis of algorithms for constructing l1 minimizing solutions to underdeter mined linear systems of full rank. It involves a relaxed min...
Enhancing Sparsity by Reweighted l1 Minimization
Iterative reweighting Underdetermined systems of linear equations Compressive sensing Dantzig selector Sparsity
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2015/7/9
It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by constraine...
A Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation
constrained ℓ 1 minimization covariance matrix Frobenius norm Gaus-sian graphical model rate of convergence precision matrix spectral norm
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2011/3/21
A constrained L1 minimization method is proposed for estimating a sparse inverse covariance matrix based on a sample of $n$ iid $p$-variate random variables. The resulting estimator is shown to enjoy ...