Algorithms for Large-scale Optimization
1.C.H. Chen, R. Chan, S. Q. Ma and J. F. Yang . Inertial proximal alternating direction method of multipliers for linearly constrained separable convex optimization. SIAM Journal on Imaging Science, 2015, 8(4), 2239-2267, 2015.
2. C. H. Chen, S. Q. Ma and J. F. Yang. A general inertial proximal point methodfor mixed variational inequality problem.SIAM Journal on Optimization, 25(4):2120–2142, 2015
3.C.H. Chen, Y. J. Liu, D. F. Sun and K. C. Toh. A Semismooth Newton-CG Based Dual PPA for Matrix Spectral Norm Approximation Problems. Mathematical Programming, Ser. A,155:435-470, 2016.
4.C.H. Chen, B.S. He, Y.Y. Ye and X.M. Yuan. The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent.Mathematical Programming,Ser. A,155:57-79, 2016.
5.C. H. Chen, M. Li, X.Liu and Y. Y. Ye. Extended ADMM and BCD for non-separable convex minimization models with quadratic coupling terms: convergenceanalysis and insights. Mathematical Programming, Ser. A, 173:37-77, 2019.
6. Q.S. Han, C.X. Li, Z.W. Lin, C.H. Chen, Q. Deng, D.D. Ge, H.K. Liu and Y.Y. Ye. A Low-Rank ADMM Splitting Approach for Semidefinite Programming. Informs Journal on Computing, 2025.
7. Q.S. Han, Z.W. Lin, H.W. Liu, C.H. Chen, Q. Deng, D.D. Ge and Y.Y. Ye. Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU. Under Revision at PNAS, 2025.
Decision Making under Uncertainty: Models and Algorithms
8. J.J. Li, C.H. Chen and A.M.C.So. Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine. NeurIPS, 2020.
9. J.J. Li, C.H. Chen and A.M.C. So. Towards a First-Order Algorithmic Framework for Wasserstein Distributionally Robust Optimization. Manuscript, 2024.
10. Y. Zhao, Z.X. Luo, S. Lim, C.H. Chen and M. Sim. Service Oriented Considerate Routing: Data, Predictions and Robust Decisions. Management Science, 2026.
11. Z.Q. Chen, C.H. Chen, J.S. Cui, Q.Hu and W. XU. Distributionally Robust Wind Planing with Decision -dependent Uncertainty. Under Revison at POMS, 2025.
Applications of Optimization in Management Science/Machine Learning
12. Y. Zhao, Y.W. Wu, C.H. Chen and A. Lim. On ismometry robustness of deep3D point cloud models under adversarial attacks. CVPR, 2020.
13. C.H. Chen, D.D. Ge, and Y.Y. Ye. Optimization and Operations Research in Mitigation of a Pandemic. Journal of the Operations Research Society of China, 2021.
14. C.H. Chen, J.H. Tao and Y. Zhan. Pairwise Stability in Weighted Network Formulation Games: Selection and Computation. Informs Journal on Computing, 2024.
15. Y.W. Wu, C.H. Chen, C.L. Chen, S.H. Jiang and A. Lim. Nonconvex Regularization for Markov Decision Processes: Modeling and Algorithms. IEEE Transcation on Automatic Control, 2025.
16. Y.D. Zhu, Y.Y. Zhu, D.Y. Dong, C.H. Chen and C.L. Chen. Conditional Diffusion Model for Multi-Agent Dynamic Task Decomposition. AAAI, 2026.
17. W.X. Chen, C.H. Chen, H.C. Shen, R.X. Wang and W.L. Xue. Dynamic Assortment with Online Learning under Threshold Multinomial Logit Model. Manuscript, 2024.
18. W.J. Shen, C.H. Chen, Z.L. Wang, Z.J. Zheng, R.W. Jiang and H. Yang. Spatiotemporal pattern detection of traffic dynamics: A robust tensor decomposition-based approach. Under Revision at Transportation Science, 2025.
20. M. Xu, C.H. Chen and H.W. Shen. Regret-Computational Efficiency Trade-off in High-dimensional Online Pricing. Under Revision at Informs Journal on Computing, 2025.
