A Unified Framework for Constructing Nonconvex Regularizations
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 19 references that are in the map. First posted on arXiv 11 Jun 2021.
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