Some projection methods with the BB step sizes for variational inequalities. - Hongjin He; Deren Han; Zhibao Li (J. Comput. Appl. Math., 2012)

A Progressive equilibration Algorithm for General Market equilibrium Problems under Constraints. - Gang Qian; Hongjin He; Deren Han (Asia Pac. J. Oper. Res., 2013)

A hybrid splitting method for variational inequality problems with separable structure. - Hongjin He; Deren Han; Wenyu Sun; Yannan Chen (Optim. Methods Softw., 2013)

A new Levenberg-Marquardt type algorithm for solving nonsmooth constrained equations. - Chen Ling 001; Guifeng Wang; Hongjin He (Appl. Math. Comput., 2014)

A proximal parallel splitting method for minimizing sum of convex functions with linear constraints. - Deren Han; Hongjin He; Lingling Xu (J. Comput. Appl. Math., 2014)

A customized Douglas-Rachford splitting algorithm for separable convex minimization with linear constraints. - Deren Han; Hongjin He; Hai Yang 003; Xiaoming Yuan 001 (Numerische Mathematik, 2014)

A fast splitting method tailored for Dantzig selector. - Hongjin He; Xingju Cai; Deren Han (Comput. Optim. Appl., 2015)

A class of nonlinear proximal point algorithms for variational inequality problems. - Hongjin He; Xingju Cai; Deren Han (Int. J. Comput. Math., 2015)

A Relaxed Projection Method for Split Variational Inequalities. - Hongjin He; Chen Ling 001; Hong-Kun Xu (J. Optim. Theory Appl., 2015)

A note on augmented Lagrangian-based parallel splitting method. - Kai Wang; Jitamitra Desai; Hongjin He (Optim. Lett., 2015)

A distributed Douglas-Rachford splitting method for multi-block convex minimization problems. - Hongjin He; Deren Han (Adv. Comput. Math., 2016)

A partially parallel splitting method for multiple-block separable convex programming with applications to robust PCA. - Liusheng Hou; Hongjin He; Junfeng Yang (Comput. Optim. Appl., 2016)

On the cone eigenvalue complementarity problem for higher-order tensors. - Chen Ling 001; Hongjin He; Liqun Qi 001 (Comput. Optim. Appl., 2016)

Higher-degree eigenvalue complementarity problems for tensors. - Chen Ling 001; Hongjin He; Liqun Qi 001 (Comput. Optim. Appl., 2016)

A primal-dual prediction-correction algorithm for saddle point optimization. - Hongjin He; Jitamitra Desai; Kai Wang (J. Glob. Optim., 2016)

An Implementable Splitting Algorithm for the ℓ1-norm Regularized Split Feasibility Problem. - Hongjin He; Chen Ling 001; Hong-Kun Xu (J. Sci. Comput., 2016)

Improved approximation results on standard quartic polynomial optimization. - Chen Ling 001; Hongjin He; Liqun Qi 001 (Optim. Lett., 2017)

A proximal partially parallel splitting method for separable convex programs. - Kai Wang; Jitamitra Desai; Hongjin He (Optim. Methods Softw., 2017)

A partially isochronous splitting algorithm for three-block separable convex minimization problems. - Hongjin He; Liusheng Hou; Hong-Kun Xu (Adv. Comput. Math., 2018)

Correction to: A partially isochronous splitting algorithm for three-block separable convex minimization problems. - Hongjin He; Liusheng Hou; Hong-Kun Xu (Adv. Comput. Math., 2018)

A Globally and Quadratically Convergent Algorithm for Solving Multilinear Systems with ℳ-tensors. - Hongjin He; Chen Ling 001; Liqun Qi 001; Guanglu Zhou (J. Sci. Comput., 2018)

Generalized tensor equations with leading structured tensors. - Weijie Yan; Chen Ling 001; Liyun Ling; Hongjin He (Appl. Math. Comput., 2019)

Generalized Tensor Complementarity Problems Over a Polyhedral Cone. - Liyun Ling; Chen Ling 001; Hongjin He (Asia Pac. J. Oper. Res., 2020)

Low-Rank and Sparse Enhanced Tucker Decomposition for Tensor Completion. - Chenjian Pan; Chen Ling 001; Hongjin He; Liqun Qi 001; Yanwei Xu (CoRR, 2020)

A Double Extrapolation Primal-Dual Algorithm for Saddle Point Problems. - Kai Wang; Hongjin He (J. Sci. Comput., 2020)

Convergence analysis of positive-indefinite proximal ADMM with a Glowinski's relaxation factor. - Jiawei Chen 004; Yiyun Wang; Hongjin He; Yibing Lv (Numer. Algorithms, 2020)

A partially proximal linearized alternating minimization method for finding Dantzig selectors. - Xiaoyu Mao; Hongjin He; Hong-Kun Xu (Comput. Appl. Math., 2021)

A DCT-based Tensor Completion Approach for Recovering Color Images and Videos from Highly Undersampled Data. - Chenjian Pan; Chen Ling 001; Hongjin He; Liqun Qi 001; Yanwei Xu (CoRR, 2021)

An index detecting algorithm for a class of TCP(A, q) equipped with nonsingular M-tensors. - Hongjin He; Xueli Bai; Chen Ling 001; Guanglu Zhou (J. Comput. Appl. Math., 2021)

A nonnegativity preserving algorithm for multilinear systems with nonsingular M-tensors. - Xueli Bai; Hongjin He; Chen Ling 001; Guanglu Zhou (Numer. Algorithms, 2021)

A customized low-rank prior model for structured cartoon-texture image decomposition. - Zhiyuan Zhang; Hongjin He (Signal Process. Image Commun., 2021)

An efficient alternating minimization method for fourth degree polynomial optimization. - Haibin Chen; Hongjin He; Yiju Wang; Guanglu Zhou (J. Glob. Optim., 2022)

A unified Douglas-Rachford algorithm for generalized DC programming. - Chih-Sheng Chuang; Hongjin He; Zhiyuan Zhang (J. Glob. Optim., 2022)

Tensor Completion via A Generalized Transformed Tensor T-Product Decomposition Without t-SVD. - Hongjin He; Chen Ling 001; Wenhui Xie (J. Sci. Comput., 2022)

Solving saddle point problems: a landscape of primal-dual algorithm with larger stepsizes. - Fan Jiang; Zhiyuan Zhang; Hongjin He (J. Glob. Optim., 2023)

A partially inexact generalized primal-dual hybrid gradient method for saddle point problems with bilinear couplings. - Kai Wang; Jintao Yu; Hongjin He (J. Appl. Math. Comput., 2023)

"Sparse + Low-Rank" tensor completion approach for recovering images and videos. - Chenjian Pan; Chen Ling 001; Hongjin He; Liqun Qi 001; Yanwei Xu (Signal Process. Image Commun., 2024)

A Partially Inertial Customized Douglas-Rachford Splitting Method for a Class of Structured Optimization Problems. - Yunfei Qu; Hongjin He; Deren Han (J. Sci. Comput., 2024)

A low-rank and sparse enhanced Tucker decomposition approach for tensor completion. - Chenjian Pan; Chen Ling 001; Hongjin He; Liqun Qi 001; Yanwei Xu (Appl. Math. Comput., 2024)

A Proximal Alternating Direction Method of Multipliers for DC Programming with Structured Constraints. - Yingxin Zhou; Hongjin He; Linan Zhang (J. Sci. Comput., 2024)

A tensor train approach for internet traffic data completion. - Zhiyuan Zhang; Chen Ling 001; Hongjin He; Liqun Qi 001 (Ann. Oper. Res., 2024)

A Unified Bregman Alternating Minimization Algorithm for Generalized DC Programs with Application to Imaging. - Hongjin He; Zhiyuan Zhang (J. Sci. Comput., 2024)

Robust tensor recovery via a nonconvex approach with ket augmentation and auto-weighted strategy. - Wenhui Xie; Chen Ling 001; Hongjin He; Lei-Hong Zhang (Numer. Linear Algebra Appl., 2024)

An Implementable Proximal Extragradient Method for Structured Fractional Programming. - Jiajun Hao; Hongjin He; Liangshao Hou (J. Optim. Theory Appl., 2025)

A multi-step inertial Bregman proximal DC algorithm and its application to solving some inverse problems. - Zhixue Wang; Chenjian Pan; Hongjin He (J. Comput. Appl. Math., 2026)