Selected publication（My co-authored works always list the authors in the alphabetical order of their names to indicate equal contributions, except the works in collaboration with mainland students due to their graduation requirements）：
R.Z. Ke and J. Zhang, On the First Order Approach for Bilevel Programming: Moral Hazard Case, preprint 2021. (pdf)
Y.W. Li, G.H. Lin, J. Zhang and X.D. Zhu, A novel approach for bilevel programs based on Wolfe duality, preprint 2021.
J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Difference of convex algorithms for bilevel programs with applications in hyperparameter selection, preprint 2021. (pdf)
R.S. Liu, P. Mu, X.M. Yuan, S.Z. Zeng and J. Zhang, A Generic Descent Aggregation Framework for Gradient-based Bi-level Optimization, preprint 2021, extension of ICML2020. (pdf)
R.S. Liu, X. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, A Hessian-free Interior-point Method for Non-convex Bilevel Optimization, preprint 2021.
L. Wang, H. Yin, J. Zhang, Density-based Distance Preserving Graph for Graph-based Learning, preprint 2021.
B. Mordukhovich, X.M. Yuan, S.Z. Zeng and J. Zhang, A globally convergent proximal Newton-type method in nonsmooth convex optimization, preprint 2020. (pdf)
R.Z. Ke, W. Yao, J.J. Ye and J. Zhang, Generic property of the partial calmness condition for bilevel programming problems, preprint 2020.
L Chen, Y.C. Liu, X.M. Yang and J. Zhang, Stochastic approximation methods for the two-stage stochastic linear complementarity problem, preprint 2020.
R.S. Liu, P. Mu and J. Zhang, Investigating Customization strategies and convergence behaviors of task-specific ADMM, preprint 2019.
R.S. Liu, L. Ma, X.M. Yuan, S.Z. Zeng and J. Zhang, Task-Oriented Convex Optimization with Latent Feasibility, preprint 2019.
J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Variational analysis perspective on linear convergence of some first order methods for nonsmooth convex optimization problems, Set-Valued and Variational Analysis, 2021, to appear
Y.C. Liu and J. Zhang, Confidence Regions of Stochastic Variational Inequalities: Error Bound Approach, Optimization, 2020, to appear. (pdf)
Y.C. Liu, X.M. Yuan and J. Zhang, Discrete Approximation Scheme in Distributionally Robust Optimization, Numerical Mathematics: Theory, Methods and Applications, 2020, to appear (pdf)
X.F. Wang, J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Perturbation techniques for convergence analysis of proximal gradient method and other first-order algorithms via variational analysis, Set-Valued and Variational Analysis, 2020, to appear (pdf)
R.S. Liu, P. Mu, X.M. Yuan, S.Z. Zeng and J. Zhang, A generic first-order algorithmic framework for bi-Level programming beyond lower-level singleton, International Conference on Machine Learning (ICML) 2020, (pdf, supplementary,slides)
C. Fang, X.Y. Ma, J. Zhang and X.D. Zhu, Personality information sharing in supply chain systems for innovative products in the circular economy era, International Journal of Production Research, 2020, to appear. (pdf)
X.M. Yuan, S.Z. Zeng and J. Zhang, Discerning the linear convergence of ADMM for structured convex optimization through the lens of variational analysis, Journal of Machine Learning Research 21, (2020) 1-75. (pdf)
J.S. Chen, J.J. Ye, J. Zhang and J.C. Zhou, Exact formula for the second-order tangent set of the second-order cone complementarity set, SIAM Journal on Optimization 29, no. 4 (2019) 2986–3011. (pdf)
K. Bai, J.J. Ye and J. Zhang, Directional quasi/pseudo-normality as sufficient conditions for metric subregularity, SIAM Journal on Optimization 29, no. 4 (2019) 2625—2647. (pdf)
Y.C. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, Partial error bound conditions and the linear convergence rate of ADMM, SIAM Journal on Numerical Analysis 56, no. 4 (2018) 2095—2123. (pdf)
Y.C. Liu, H.F. Xu, S. Yang and J. Zhang, Distributionally robust equilibrium for continuous games: Nash and Stackelberg models, European Journal of Operational Research 265 no. 2 (2018) 631—643.(pdf)
Y.C. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, Primal-dual hybrid gradient method for distributionally robust optimization problem, Operational Research Letters 45 no. 6, (2017) 625—630.(pdf)
G.H. Lin, M.J. Luo, D.L. Zhang and J. Zhang, Stochastic second-order-cone complementarity problems: expected residual minimization formulation and its applications, Mathematical Programming, 165, no.1 (2017), 197-233. (pdf)
G.H. Lin, M.J. Luo and J. Zhang, Smoothing and SAA method for stochastic programming problems with non-smooth objective and constraints. Journal of Global Optimization 66, no. 3 (2016), 487--510.
L. Guo, G.H. Lin, J.J. Ye and J. Zhang, Sensitivity analysis of the value function for parametric mathematical programs with equilibrium constraints. SIAM Journal on Optimization, 24, no. 3 (2014), 1206--1237. (pdf)
J.J. Ye and J. Zhang, Enhanced Karush-Kuhn-Tucker conditions for mathematical programs with equilibrium constraints. Journal of Optimization Theory and Applications 163, no. 3 (2014), 777--794. (pdf)
L. Guo, J.J. Ye and J. Zhang, Mathematical programs with geometric constraints in Banach spaces: enhanced optimality, exact penalty, and sensitivity. SIAM Journal on Optimization, 23, no. 4, (2013), 2295--2319. (pdf)
J.J. Ye and J. Zhang, Enhanced Karush-Kuhn-Tucker condition and weaker constraint qualifications. Mathematical Programming, 139, no. 1-2 (2013), 353--381. (pdf)
Publications with mainland students supervised and co-supervised
R.S. Liu, J.X. Gao, J. Zhang, D.Y. Meng and Z.C. Lin, Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond, preprint 2021.
Z.P. Yang, J. Zhang, Y.L. Wang and G.H. Lin, Variance-Based Subgradient Extragradient Method for Stochastic Variational Inequality Problems, Journal of Scientific Computing, 2020, to appear
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, Some kind of Pareto stationarity for multiobjective problems with equilibrium constraints, Optimization, (2019) doi:10.1080/02331934.2019.1591406
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, New Constraint Qualifications for S-Stationarity for MPEC with Nonsmooth Objective, Asia Pacific Journal of Operational Research, (2019), DOI: 10.1142/S0217595919400013
X.D. Zhu, J. Zhang, J.C. Zhou and X.M. Yang, Mathematical programs with second-order cone complementarity constraints: strong stationarity and approximation method, Journal of Optimization Theory and Applications, (2019). doi.org/10.1007/s10957-018-01464-w
Z.P. Yang, J. Zhang, X.D. Zhu and G.H. Lin, SAA-based infeasible interior-point algorithms for a class of stochastic complementarity problems and their applications, Journal of Computational and Applied Mathematics, 352, (2019) 382—400
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, Constraint qualifications and proper Pareto optimality conditions for multiobjective problem with equilibrium constraints, Journal of Optimization Theory and Applications, 176 no. 3 (2018) 763—782
G.X. Wang, J. Zhang, B. Zeng and G.H. Lin, Expected residual minimization formulation for a class of stochastic linear second-order cone complementarity problems, European Journal of Operational Research 265 no. 2 (2018). 437—447
S.H. Jiang, J. Zhang, C.H. Chen and G.H. Lin, Smoothing partial exact penalty splitting method for mathematical programs with equilibrium constraints, Journal of Global Optimization, (2017). DOI: 10.1007/s10898-017-0539-4
Y. Zhao, J. Zhang, X.M. Yang and G.H. Lin, Expected residual minimization formulation for a class of stochastic vector variational inequalities. Journal of Optimization Theory and Applications 175 no. 2 (2017), 545--566.
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