References in zbMATH (referenced in 76 articles )

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  1. Hu, Wenyu; Lu, Yao; Ren, Jin: A fixed-point proximity algorithm for recovering low-rank components from incomplete observation data with application to motion capture data refinement (2022)
  2. Zhao, Jianxi: A novel low-rank matrix approximation algorithm for face denoising and background/foreground separation (2022)
  3. Chen, Yuxin; Fan, Jianqing; Ma, Cong; Yan, Yuling: Bridging convex and nonconvex optimization in robust PCA: noise, outliers and missing data (2021)
  4. Li, Qinxue; Li, Shanbin; Xu, Bugong; Liu, Yonggui: Data-driven attacks and data recovery with noise on state estimation of smart grid (2021)
  5. Ma, Feng; Shu, Jiansheng; Li, Yaxiong; Wu, Jian: The dual step size of the alternating direction method can be larger than 1.618 when one function is strongly convex (2021)
  6. Shen, Yuan; Zhang, Xingying; Zhang, Xiayang: A partial PPA block-wise ADMM for multi-block linearly constrained separable convex optimization (2021)
  7. Shen, Yuan; Zuo, Yannian; Zhang, Xiayang: A faster generalized ADMM-based algorithm using a sequential updating scheme with relaxed step sizes for multiple-block linearly constrained separable convex programming (2021)
  8. Yang, Jun-Feng; Zhang, Yin: Local linear convergence of an ADMM-type splitting framework for equality constrained optimization (2021)
  9. Yashtini, Maryam: Multi-block nonconvex nonsmooth proximal ADMM: convergence and rates under Kurdyka-Łojasiewicz property (2021)
  10. Dong, Jing; Xue, Zhichao; Wang, Wenwu: Robust PCA using nonconvex rank approximation and sparse regularizer (2020)
  11. Dornaika, F.; Khoder, A.: Linear embedding by joint robust discriminant analysis and inter-class sparsity (2020)
  12. Galvan, G.; Lapucci, M.; Levato, T.; Sciandrone, M.: An alternating augmented Lagrangian method for constrained nonconvex optimization (2020)
  13. Shen, Yuan; Liu, Xin: An alternating minimization method for matrix completion problems (2020)
  14. Wei, Ke; Cai, Jian-Feng; Chan, Tony F.; Leung, Shingyu: Guarantees of Riemannian optimization for low rank matrix completion (2020)
  15. Wen, Ruiping; Fu, Yaru: Toeplitz matrix completion via a low-rank approximation algorithm (2020)
  16. Zhao, Jianxi; Zhao, Lina: Low-rank and sparse matrices fitting algorithm for low-rank representation (2020)
  17. Ansary Karbasy, Saeid; Salahi, Maziar: A hybrid algorithm for the two-trust-region subproblem (2019)
  18. Dong, Zhengshan; Chen, Jianli; Zhu, Wenxing: Homotopy method for matrix rank minimization based on the matrix hard thresholding method (2019)
  19. Driggs, Derek; Becker, Stephen; Aravkin, Aleksandr: Adapting regularized low-rank models for parallel architectures (2019)
  20. Jiang, Bo; Lin, Tianyi; Ma, Shiqian; Zhang, Shuzhong: Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis (2019)

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