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SSG Seminar Abstract


Recovery of Sparse Signals and Shifting Inequality

Prof. Lie Wang
MIT


We present a concise and coherent analysis of the constrained l1 minimization method for stable recovering of high-dimensional sparse signals both in the noiseless case and noisy case. The analysis is surprisingly simple and elementary, while leads to strong results. In particular, it is shown that the sparse recovery problem can be solved via l1 minimization under weaker conditions than what is known in the literature. An oracle inequality is also derived.



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