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A Unified Framework for Constructing Nonconvex Regularizations (2106.06123v1)

Published 11 Jun 2021 in stat.ML, cs.IT, cs.LG, and math.IT

Abstract: Over the past decades, many individual nonconvex methods have been proposed to achieve better sparse recovery performance in various scenarios. However, how to construct a valid nonconvex regularization function remains open in practice. In this paper, we fill in this gap by presenting a unified framework for constructing the nonconvex regularization based on the probability density function. Meanwhile, a new nonconvex sparse recovery method constructed via the Weibull distribution is studied.

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