Publications

Preprints

• Jiang J, Chen Z, Yang X. Rates of convergence of sample average approximation under heavy tailed distributions, 2020.
  

• Jiang J, Li S. Stochastic Minimax Problems: Quantification, Optimality and Numerical Results, 2021.
  

Selected Journal Papers

1. Chen Z, Jiang J. Stability analysis of optimization problems with kth order stochastic and distributionally robust dominance constraints induced by full random recourse. SIAM Journal on Optimization, 2018, 28(2): 1396-1419.
   

2. Jiang J, Shi Y, Wang X, Chen X. Regularized two-stage stochastic variational inequalities for Cournot-Nash equilibrium under uncertainty. Journal of Computational Mathematics, 2019, 37(6): 813-842.
   

3. Jiang J, Chen X, Chen Z. Quantitative analysis for a class of two-stage stochastic linear variational inequality problems. Computational Optimization and Applications, 2020, 76(2): 431–460.
   

4. Jiang J, Sun H, Zhou B. Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage. Numerical Algorithms, 2022, 89(1): 167-194
   

5. Peng S, Jiang J. Stochastic mathematical programs with probabilistic complementarity constraints: SAA and distributionally robust approaches. Computational Optimization and Applications, 2021, 80(1): 153–184.
   

6. Jiang J, Li S. Regularized sample average approximation approach for two-stage stochastic variational inequalities. Journal of Optimization Theory and Applications, 2021, 190(2): 650–671.
   

7. Jiang J, Chen X. Pure Characteristics Demand Models and Distributionally Robust Mathematical Programs with Stochastic Complementarity Constraints. Mathematical Programming, 2023, 198: 1449–1484.
   

8. Jiang J, Sun H. Monotonicity and complexity of multistage stochastic variational inequalities. Journal of Optimization Theory and Applications, 2023, 196: 433-460.
   

9. Jiang J, Chen X. Optimality conditions for nonsmooth nonconvex-nonconcave min-max problems and generative adversarial networks. SIAM Journal on Mathematics of Data Science, 2023, 5(3): 693-722.
   

10. Jiang J, Peng S. Mathematical programs with distributionally robust chance constraints: Statistical robustness, discretization and reformulation. European Journal of Operational Research, 2024, 313(2): 616-627.
    

11. Jiang J, Sun H. Discrete approximation for two-stage stochastic variational inequalities. Journal of Global Optimization, 2024, 89: 117–142.
    

12. Zhou B, Jiang J, Song Y, Sun H. Variance-based stochastic projection gradient method for two-stage co-coercive stochastic variational inequalities. Numerical Algorithms, 2024.
    

13. Jiang J, Sun H, Chen X. Data-driven distributionally robust multiproduct pricing problems under pure characteristics demand models. SIAM Journal on Optimization, 2024, 34(3): 2917-2942.
    

14. Zhou B, Jiang J, Sun H. Dynamic stochastic projection method for multistage stochastic variational inequalities. Computational Optimization and Applications, 2024, 89: 485-516.
    

15. Jiang J. Distributionally robust variational inequalities: Relaxation, quantification and discretization. Journal of Optimization Theory and Applications, 2024, 203: 227-255.
    

16. Qiu Z, Jiang J, Chen X. A quasi-Newton subspace trust region algorithm for nonmonotone variational inequalities in adversarial learning over box constraints. Journal of Scientific Computing, 2024, 101.