Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models

IEEE J. Sel. Areas Inf. Theory, pp. 292-303, 2020.

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Abstract:

The goal of standard compressive sensing is to estimate an unknown vector from linear measurements under the assumption of sparsity in some basis. Recently, it has been shown that significantly fewer measurements may be required if the sparsity assumption is replaced by the assumption that the unknown vector lies near the range of a sui...More

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