Volume 18, Number 2, 2022
Contents

Special Issue on Numerical Optimization in Data Science

Preface: Zheng-Hai Huang, Lingchen Kong and Yiju Wang

Hongwu Li, Haibin Zhang and Yunhai Xiao
An accelerated gradient method for nonconvex sparse subspace clustering problem

Kaiping Liu and Haitao Che
Tighter eigenvalue localization sets for fourth-order partially symmetric tensor and its applications

Yong Jin Liu and Qinxin Zhu
A semismooth Newton based augmented Lagrangian algorithm for Weber problem

 
Zai Yun Peng, Xian Jun Long, Jing Zeng and Zhi Lin
On the stability of approximate solution mappings to generalized Ky Fan inequality

Yifan Shao, Qingsong Wang and Deren Han
Efficient methods for convex problems with Bregman Barzilai-Borwein step sizes


Jun Sun, Pan Shang, Qiuyun Xu and Bingzhen Chen
Multivariate linear regression with low-rank and row-sparsity

Chunming Tang, Huangyue Chen, Jinbao Jian and Shuai Liu
A bundle-type quasi-Newton method for nonconvex nonsmooth optimization

Jie Wang
Von Neumann-type inequality for completely orthogonally decomposable tensors

Tanxing Wang, Xingju Cai, Yongzhong Song and Xue Gao
Double-inertial proximal gradient algorithm for difference-of-convex programming

Yangxin Wei, Ziyan Luo and Yang Chen
Image space branch-and-bound algorithm for globally solving minimax linear fractional programming problem

Yingrang Xu and Shengjie Li
Höder continuity results for parametric set optimization problems via improvement sets

 
Junwei Zhang and Yuning Yang
Hybrid alternating extra-gradient and Newton’s method for tensor decomposition

Danqing Zhou, Xiaokai Chang and Junfeng Yang
A new primal-dual algorithm for structured convex optimization involving a Lipschitzian term

 
   
   
   
   
   
   

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