References in zbMATH (referenced in 93 articles )

Showing results 1 to 20 of 93.
Sorted by year (citations)

1 2 3 4 5 next

  1. Cheng, Wanyou; Dai, Yu-Hong: An active set Newton-CG method for (\ell_1) optimization (2021)
  2. Wang, Jin-Ju; Huang, Ting-Zhu; Huang, Jie; Deng, Liang-Jian: A two-step iterative algorithm for sparse hyperspectral unmixing via total variation (2021)
  3. Wang, Lizhi; Zhang, Shipeng; Huang, Hua: Adaptive dimension-discriminative low-rank tensor recovery for computational hyperspectral imaging (2021)
  4. Kikuchi, Paula A.; Oliveira, Aurelio R. L.: New preconditioners applied to linear programming and the compressive sensing problems (2020)
  5. Shen, Chungen; Xue, Wenjuan; Zhang, Lei-Hong; Wang, Baiyun: An active-set proximal-Newton algorithm for (\ell_1) regularized optimization problems with box constraints (2020)
  6. Cheng, Wanyou; Hu, Qingjie; Li, Donghui: A fast conjugate gradient algorithm with active set prediction for (\ell_1) optimization (2019)
  7. Esmaeili, Hamid; Shabani, Shima; Kimiaei, Morteza: A new generalized shrinkage conjugate gradient method for sparse recovery (2019)
  8. Feng, Lei; Sun, Huaijiang; Zhu, Jun: Robust image compressive sensing based on half-quadratic function and weighted Schatten-(p) norm (2019)
  9. Figueiredo, Mário A. T.: On the use of ADMM for imaging inverse problems: the pros and cons of matrix inversions (2019)
  10. Li, Qian; Bai, Yanqin; Yu, Changjun; Yuan, Ya-xiang: A new piecewise quadratic approximation approach for (L_0) norm minimization problem (2019)
  11. Liu, Zexian; Liu, Hongwei; Wang, Xiping: Accelerated augmented Lagrangian method for total variation minimization (2019)
  12. Maass, Peter: Deep learning for trivial inverse problems (2019)
  13. Rahpeymaii, Farzad; Amini, Keyvan; Allahviranloo, Tofigh; Malkhalifeh, Mohsen Rostamy: A new class of conjugate gradient methods for unconstrained smooth optimization and absolute value equations (2019)
  14. Shen, Yuan; Ji, Lei: Partial convolution for total variation deblurring and denoising by new linearized alternating direction method of multipliers with extension step (2019)
  15. Tavakkol, E.; Hosseini, S. M.; Hosseini, A. R.: A new regularization term based on second order total generalized variation for image denoising problems (2019)
  16. Wu, Caiying; Zhan, Jiaming; Lu, Yue; Chen, Jein-Shan: Signal reconstruction by conjugate gradient algorithm based on smoothing (l_1)-norm (2019)
  17. Xu, Yuesheng; Ye, Qi: Generalized Mercer kernels and reproducing kernel Banach spaces (2019)
  18. Zhou, Yu; Guo, Hainan: Collaborative block compressed sensing reconstruction with dual-domain sparse representation (2019)
  19. Barbero, Álvaro; Sra, Suvrit: Modular proximal optimization for multidimensional total-variation regularization (2018)
  20. Cheng, Wanyou; Dai, Yu-Hong: Gradient-based method with active set strategy for (\ell_1) optimization (2018)

1 2 3 4 5 next