The Generalized Lasso with Nonlinear Observations and Generative Priors

NIPS 2020, 2020.

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We have provided recovery guarantees for the generalized Lasso with nonlinear observations and generative priors

Abstract:

In this paper, we study the problem of signal estimation from noisy non-linear measurements when the unknown $n$-dimensional signal is in the range of an $L$-Lipschitz continuous generative model with bounded $k$-dimensional inputs. We make the assumption of sub-Gaussian measurements, which is satisfied by a wide range of measurement mo...More

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