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Tractable Evaluation of Stein's Unbiased Risk Estimate with Convex Regularizers - MaRDI portal

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Tractable Evaluation of Stein's Unbiased Risk Estimate with Convex Regularizers

From MaRDI portal
Publication:6416879

arXiv2211.05947MaRDI QIDQ6416879

Author name not available (Why is that?)

Publication date: 10 November 2022

Abstract: Stein's unbiased risk estimate (SURE) gives an unbiased estimate of the ell2 risk of any estimator of the mean of a Gaussian random vector. We focus here on the case when the estimator minimizes a quadratic loss term plus a convex regularizer. For these estimators SURE can be evaluated analytically for a few special cases, and generically using recently developed general purpose methods for differentiating through convex optimization problems; these generic methods however do not scale to large problems. In this paper we describe methods for evaluating SURE that handle a wide class of estimators, and also scale to large problem sizes.




Has companion code repository: https://github.com/cvxgrp/sure-cr








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