A p-SPHERICAL SECTION PROPERTY FOR MATRIX SCHATTEN-p QUASI-NORM MINIMIZATION

被引：0
|
作者：
Feng, Yifu [1 ]
Zhang, Min [2 ,3 ]
机构：
[1] Jilin Normal Univ, Coll Math, Siping 136000, Jilin, Peoples R China
[2] Chongqing Normal Univ, Sch Math Sci, Chongqing 401131, Peoples R China
[3] Curtin Univ, Sch Elec Engn Comp & Math Sci EECMS, Bentley, WA 6102, Australia
来源：
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION | 2020年 / 16卷 / 01期
关键词：
Low-rank matrix recovery; Schatten-p minimization; spherical section property; SPARSE REPRESENTATION; RANK; RECOVERY;
D O I：
10.3934/jimo.2018159
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Low-rank matrix recovery has become a popular research topic with various applications in recent years. One of the most popular methods to dual with this problem for overcoming its NP-hardness is to relax it into some tractable optimization problems. In this paper, we consider a nonconvex relaxation, the Schatten-p quasi-norm minimization (0 < p < 1), and discuss conditions for the equivalence between the original problem and this nonconvex relaxation. Specifically, based on null space analysis, we propose a p-spherical section property for the exact and approximate recovery via the Schatten-p quasi-norm minimization (0 < p < 1).
引用
收藏
页码：397 / 407
页数：11
相关论文
共 50 条
  • [21] Efficient DOA Estimation for Coprime Array via Bi-Nuclear Schatten-p Norm Minimization
    Jiang, Siyuan
    Liu, Shuai
    Jin, Ming
    Yan, Feng-Gang
    Lin, Zhiping
    IEEE SIGNAL PROCESSING LETTERS, 2025, 32 : 866 - 870
  • [22] Bi-Nuclear Tensor Schatten-p Norm Minimization for Multi-View Subspace Clustering
    Wang, Shuqin
    Lin, Zhiping
    Cao, Qi
    Cen, Yigang
    Chen, Yongyong
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 32 : 4059 - 4072
  • [23] Image Recovery via Truncated Weighted Schatten-p Norm Regularization
    Feng, Lei
    Zhu, Jun
    CLOUD COMPUTING AND SECURITY, PT VI, 2018, 11068 : 563 - 574
  • [24] Image compressive sensing via Truncated Schatten-p Norm regularization
    Feng, Lei
    Sun, Huaijiang
    Sun, Quansen
    Xia, Guiyu
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2016, 47 : 28 - 41
  • [25] Robust Subspace Clustering Based on Latent Low-rank Representation with Weighted Schatten-p Norm Minimization
    Qu, Qin
    Wang, Zhi
    Chen, Andwu
    PRICAI 2022: TRENDS IN ARTIFICIAL INTELLIGENCE, PT I, 2022, 13629 : 504 - 515
  • [26] Multi -View Subspace Clustering based on Tensor Schatten-p Norm
    Liu, Yongli
    Zhang, Xiaoqin
    Tang, Guiying
    Wang, Di
    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 5048 - 5055
  • [27] FOCUSS Based Schatten-p Norm Minimization for Real-Time Reconstruction of Dynamic Contrast Enhanced MRI
    Majumdar, Angshul
    IEEE SIGNAL PROCESSING LETTERS, 2012, 19 (05) : 315 - 318
  • [28] Sparse Data-Driven Quadrature Rules via l p -Quasi-Norm Minimization
    Manucci, Mattia
    Aguado, Jose Vicente
    Borzacchiello, Domenico
    COMPUTATIONAL METHODS IN APPLIED MATHEMATICS, 2022, 22 (02) : 389 - 411
  • [29] Compressive Sensing of Multichannel EEG Signals via lq Norm and Schatten-p Norm Regularization
    Zhu, Jun
    Chen, Changwei
    Su, Shoubao
    Chang, Zinan
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2016, 2016
  • [30] Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization
    Nie, Feiping
    Wang, Hua
    Cai, Xiao
    Huang, Heng
    Ding, Chris
    12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2012), 2012, : 566 - 574
12345