Optimal deep neural networks for sparse recovery via Laplace techniques

4 Sep 2017Steffen LimmerSlawomir Stanczak

This paper introduces Laplace techniques for designing a neural network, with the goal of estimating simplex-constraint sparse vectors from compressed measurements. To this end, we recast the problem of MMSE estimation (w.r.t... (read more)

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