代表性成果与荣誉
发表的论文（部分）：
1 Efficient dual ADMMs for sparse compressive sensing MRI reconstruction. Yanyun Ding, Peili Li, Yunhai Xiao, Haibin Zhang, Mathematical Methods of Operations Research, DOI: 10.1007/s00186-023-00811-6，2023;
2An efficient semismooth Newton method for adaptive sparse signal reconstruction problems, Yanyun Ding, Haibin Zhang, Peili Li, Yunhai Xiao, Optimization Methods and Software, 2023, 38(2): 262-288;
3 A tight bound of modified iterative hard thresholding algorithm for compressed sensing, Jinyao Ma, Haibin Zhang, Shanshan Yang, and Jiaojiao Jiang, Applications of Mathematics, DOI：10.21136/AM.2023.0221-22, 2023;
4 An accelerated regularized Chebyshev-Halley method for unconstrained optimization, Jianyu Xiao, Haibin Zhang, and Huan Gao, Asia-Pacific Journal of Operational Research, DOI：10.1142/S0217595923400080，2023;
5 Platform resource scheduling method based on branch-and-bound and genetic algorithm, Yanfen Zhang, Jinyao Ma, Haibin Zhang, ang Bin Yue, Annals of Data Science, DOI：10.1007/s40745-023-00470-8，2023;
6 An adaptive l1-l2-type model with hierarchies for sparse signal reconstruction problem, Yanyun Ding, Zhixiao Yue, and Haibin Zhang, Pacific Journal of Optimization, (2022), 18(4): 695-712;
7 Stochastic proximal difference of convex algorithm with SPIDER for a class of nonvex nonsmooth regularized problems，Kai Tu, Haibin Zhang, and Huan Gao，Journal of Nonlinear and Convex Analysis (2020) 21:1191-1208；
8 A hybrid Bregman alternating direction method of Multipliers for the linearly constrained difference-of-convex problems, Kai Tu, Haibin Zhang, Huan Gao，and Feng Junkai, Journal of Global Optimization (2020)76:665–693;
9 Sparse multiple instance learning with non-convex penalty，Yuqi Zhang, Haibin Zhang, and Yingjie Tian, Neurocomputing (2020) 391: 142-156.
10 A modified nonlinear conjugate gradient algorithm for large-scale nonsmooth convex optimization, T. G., Woldu, Haibin Zhang, and Xin Zhang. Journal of Optimization Theory and Applications, (2020) 185(1): 1-16.
11 A new alternating projection-based prediction–correction method for structured variational inequalities, Kai Tu, Haibin Zhang, and Fuquan Xia，Optimization Methods and Software (2019) 34(4): 707-730.
12 An iterative scheme for testing the positive definiteness of multivariate homogeneous forms, Kaili Zhang, Haibin Zhang, and Pengfei Zhao. International Journal of Computer Mathematics, (2019) 96(12): 2461-2472.
13 Proximal gradient method with automatic selection of the parameter by automatic differentiation, Yingyi Li, Haibin Zhang, and Zhibao Li. Optimization Methods and Software, (2018) 33(4-6): 708-717.
14 A nonmonotone inexact Newton method for unconstrained optimization, Huan Gao, Haibin Zhang, and Zhibao Li, Optimization Letters (2017) 11: 947–965;
15 On the proximal Landweber Newton method for a class of nonsmooth convex problems，Haibin Zhang, Jiaojiao Jiang, and Yunbin Zhao, Computational Optimization and Applications (2015) 61:79–99;
16 A Linearized Alternating Direction Method of Multipliers with Substitution Procedure, Miantao Chao, Caozong Cheng, and Haibin Zhang, Asia-Pacific Journal of Operational Research (2015) 32(3);
17 Convergence Analysis of L-ADMM for Multi-block Linear-Constrained Separable Convex Minimization Problem, Junkai Feng, and Haibin Zhang，Journal of the Operations Research Society of China (2015)3: 563-575;
18 On Proximal Gradient Method for the Convex Problems Regularized with the Group Reproducing Kernel Norm，Haibin Zhang, Juan Wei, Meixia Li, Jie Zhou, and Miantao Chao, Journal of Global Optimization (2014) 58(1): 169-188;
19 A proximal classifier with positive and negative local regions, Yuanhai Shao, Weijie Chen, Zhen Wang, Haibin Zhang, and Naiyang Deng, Neurocomputing (2014) 145: 131-139;
20 On the Linear Convergence of a Proximal Gradient Method for a Class of Nonsmooth Convex Minimization Problems, Haibin Zhang, Jiaojiao Jiang, and Zhiquan Luo，Journal of Operations Research Society of China (2013) 1(2): 163-186;
21 An interior point trust region method for nonnegative matrix factorization, Jiaojiao Jiang,Haibin Zhang, and Shui Yu, Neurocomputing (2012)97: 309-316;
22 On the Halley class of methods for unconstrained optimization problems, Haibin Zhang, Optimization Methods and Software (2010) 25(5):753-762;
23 An improved inexact Newton method, Haibin Zhang and Naiyang Deng, Journal of Global Optimization (2007)39: 221-234;
出版的著作：
自动微分方法与最优化，张海斌,高欢，科学出版社，ISBN:9787030471017, 2016;
凸优化理论与算法，张海斌，张凯丽，科学出版社，ISBN:9787030655745，2020
