Structured Sparsity Optimization with Non-Convex Surrogates of $\ell _{2,0}$-Norm: A Unified Algorithmic Framework-Reference-Cited by-同舟云学术

Structured Sparsity Optimization with Non-Convex Surrogates of $\ell _{2,0}$-Norm: A Unified Algorithmic Framework

Author:

Zhang Xiaoqin¹^ORCID,Zheng Jingjing¹,Wang Di²^ORCID,Tang Guiying¹,Zhou Zhengyuan³^ORCID,Lin Zhouchen⁴^ORCID

Affiliation:

1. College of Computer Science and Artificial Intelligence, Wenzhou University, China

2. Center for Intelligent Decision-Making and Machine Learning, School of Management, Xi'an Jiaotong University, Xi'an, China

3. Department of Electrical Engineering, Stanford University, Stanford, USA

4. Key Laboratory of Machine Perception (MOE), School of Intelligence Science and Technology, Peking University, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

Reference77 articles.

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