References in zbMATH (referenced in 65 articles )

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  1. Esmaeili, Hamid; Shabani, Shima; Kimiaei, Morteza: A new generalized shrinkage conjugate gradient method for sparse recovery (2019)
  2. Li, Qian; Bai, Yanqin; Yu, Changjun; Yuan, Ya-xiang: A new piecewise quadratic approximation approach for (L_0) norm minimization problem (2019)
  3. 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)
  4. Barbero, Álvaro; Sra, Suvrit: Modular proximal optimization for multidimensional total-variation regularization (2018)
  5. Cheng, Wanyou; Dai, Yu-Hong: Gradient-based method with active set strategy for (\ell_1) optimization (2018)
  6. Iutzeler, Franck; Malick, Jérôme: On the proximal gradient algorithm with alternated inertia (2018)
  7. Ülkü, İrem; Kizgut, Ersin: Large-scale hyperspectral image compression via sparse representations based on online learning (2018)
  8. Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.: Total variation superiorized conjugate gradient method for image reconstruction (2018)
  9. Buccini, Alessandro: Regularizing preconditioners by non-stationary iterated Tikhonov with general penalty term (2017)
  10. Gong, Maoguo; Jiang, Xiangming; Li, Hao: Optimization methods for regularization-based ill-posed problems: a survey and a multi-objective framework (2017)
  11. Jensen, T. L.; Diehl, Moritz: An approach for analyzing the global rate of convergence of quasi-Newton and truncated-Newton methods (2017)
  12. Jiang, Daijun; Liu, Yikan; Yamamoto, Masahiro: Inverse source problem for the hyperbolic equation with a time-dependent principal part (2017)
  13. Karimi, Sahar; Vavasis, Stephen: IMRO: A proximal quasi-Newton method for solving (\ell_1)-regularized least squares problems (2017)
  14. Liu, Lingjun; Xie, Zhonghua; Feng, Jiuchao: Backtracking-based iterative regularization method for image compressive sensing recovery (2017)
  15. Oktem, Figen S.; Gao, Liang; Kamalabadi, Farzad: Computational spectral and ultrafast imaging via convex optimization (2017)
  16. Pereyra, Marcelo: Maximum-a-posteriori estimation with Bayesian confidence regions (2017)
  17. Rao, Vishwas; Sandu, Adrian; Ng, Michael; Nino-Ruiz, Elias D.: Robust data assimilation using (L_1) and Huber norms (2017)
  18. Byrd, Richard H.; Chin, Gillian M.; Nocedal, Jorge; Oztoprak, Figen: A family of second-order methods for convex (\ell_1)-regularized optimization (2016)
  19. Chen, Dai-Qiang; Zhou, Yan; Song, Li-Juan: Fixed point algorithm based on adapted metric method for convex minimization problem with application to image deblurring (2016)
  20. De Santis, Marianna; Lucidi, Stefano; Rinaldi, Francesco: A fast active set block coordinate descent algorithm for (\ell_1)-regularized least squares (2016)

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