Survey on Group Sparse Models and Algorithms

LIU Jian-wei; CUI Li-peng; LUO Xiong-lin

doi:10.3969/j.issn.0372-2112.2015.04.021

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Survey on Group Sparse Models and Algorithms

更新时间：2025-07-16

- Survey on Group Sparse Models and Algorithms
- Acta Electronica Sinica Vol. 43, Issue 4, Pages: 776-782(2015)
- 作者机构：
  
  中国石油大学(北京)自动化研究所,北京,102249
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.21006127)
- DOI：10.3969/j.issn.0372-2112.2015.04.021
  CLC： TP181
- Published：2015
- 稿件说明：
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LIU Jian-wei, CUI Li-peng, LUO Xiong-lin. Survey on Group Sparse Models and Algorithms[J]. Acta Electronica Sinica, 2015, 43(4): 776-782.
DOI：

LIU Jian-wei, CUI Li-peng, LUO Xiong-lin. Survey on Group Sparse Models and Algorithms[J]. Acta Electronica Sinica, 2015, 43(4): 776-782. DOI： 10.3969/j.issn.0372-2112.2015.04.021.

摘要

稀疏性与组稀疏性在统计学、信号处理和机器学习等领域中具有重要的应用.本文总结和分析了不同组稀疏模型之间的区别与联系

比较了不同组稀疏模型的变量选择能力、变量组选择能力、变量选择一致性和变量组选择一致性

总结了组稀疏模型的各类求解算法并指出了各算法的优点和不足.最后

本文对组稀疏模型未来的研究方向进行了探讨.

Abstract

The sparsity and group sparsity have important applications in the statistics

signal processing and machine learning.This paper summarized and analyzed the differences and relations between various group sparse models.In addition

we compared different models' variable selection ability

variable group selection ability

variable selection consistency and variable group selection consistency.We also summarized the algorithms of group sparse models and pointed the advantages and disadvantages of the algorithms.Finally

we point out the future research directions of the group sparse models.

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