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Solving under-determined systems of linear equations with sparse solutions attracted enormous amount of attention in recent years, above all, due to work of \cite{CRT,CanRomTao06,DonohoPol}.
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Discussion: The dantzig selector: statistical estimation when p p is much larger than n n
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One sketch for all: fast algorithms for compressed sensing
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Highly sparse representations from dictionaries are unique and independent of the sparseness measure
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Compressed sensing meets bionformatics: a new DNA microarray architecture
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Imaging via compressive sampling
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Dasso: Connections between the dantzig selector and lasso
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CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
D. Needell and J. A. Tropp · 2009
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Unifrom uncertainly principles and signal recovery via regularized orthogonal matching pursuit
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Various thresholds for ℓ 1 \ell_{1} -optimization in compressed sensing
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On the lasso and dantzig selector equivalence
M. S. Asif and J. Romberg · 2010
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The noise-sensitiviy thase transition in compressed sensing
D. Donoho, A. Maleki, and A. Montanari · 2010
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