mlsanityData to 14 Oct 2026

A Unified Framework for Constructing Nonconvex Regularizations

arXiv 2106.06123 ↗First posted 11 Jun 2021stat.ML cs.IT cs.LGcited by 0

Not on the map. Why?

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.

Builds on

2 of 19 references.

References · 2

  1. 2020A Novel Regularization Based on the Error Function for Sparse Recoverycited by 8
  2. 2021Sparse recovery based on the generalized error functioncited by 1

Built on by

Not cited yet.