Rujun Jiang (江如俊)

Associate Professor
School of Data Science
Fudan University
No. 220 Handan Road, Shanghai 200433

Office: N202, Zibin Building
Email: rjjiang@fudan.edu.cn

Background

Rujun Jiang is currently an associate professor at School of Data Science, Fudan University. He received his Bachelor degree in Mathematics in 2012 from University of Science and Technology of China. He then obtained his PhD degree in 2016 in The Chinese University of Hong Kong under the supervision of Professor Duan Li. Before joining Fudan in 2017, He spent one year in CUHK as a postdoctoral fellow. He has received an ICML Outstanding Paper Award (2022).

Postdoc and graduate student positions available

Teaching

DATA620008: Optimization Theory and Methods

DATA130026: Numerical Optimization

Research Interest

Optimization methods and theory and their applications in operations research, machine learning and signal processing
Current focus

Preprints

  1. Pengyu Chen, Xu Shi, Rujun Jiang, Jiulin Wang. Penalty-based Methods for Simple Bilevel Optimization under H\"{o}lderian Error Bounds. arXiv preprint arXiv:2402.02155, 2024
  2. Chenyu Zhang and Rujun Jiang. Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians. arXiv preprint arXiv:2309.04052, 2023
  3. Chenyu Zhang, Rufeng Xiao, Wen Huang, Rujun Jiang. Riemannian Trust Region Methods for SC1 Minimization. arXiv preprint arXiv:2307.00490, 2023
  4. Peng Wang, Rujun Jiang, Qingyuan Kong and Laura Balzano. Difference-of-Convex Reformulation for Chance Constrained Programs. arXiv preprint arXiv:2301.00423, 2023
  5. Xiangyu Cui, Rujun Jiang, Yun Shi, Yifan Yan. Decision Making under Cumulative Prospect Theory: An Alternating Direction Method of Multipliers. arXiv preprint arXiv:2210.02626, 2022
  6. Alex L. Wang and Rujun Jiang. New notions of simultaneous diagonalizability of quadratic forms with applications to QCQPs. arXiv preprint arXiv:2101.12141, 2021. code

Journal Articles

  1. Wutao Si, P.-A. Absil, Wen Huang, Rujun Jiang and Simon Vary. A Riemannian Proximal Newton Method. SIAM Journal on Optimization 34.1 (2024), 654-681.
  2. Rujun Jiang and Duan Li. Exactness Conditions for Semidefinite Programming Relaxations of Generalization of the Extended Trust Region Subproblem. Mathematics of Operations Research. 48.3 (2023): 1235-1253. doi/abs/10.1287/moor.2022.1305
  3. Rujun Jiang, Zhizhuo Zhou and Zirui Zhou. Cubic Regularization Methods with Second-Order Complexity Guarantee Based on a New Subproblem Reformulation. Journal of the Operations Research Society of China. 10 (2022): 471–506. https://doi.org/10.1007/s40305-022-00398-5
  4. Rujun Jiang and Xudong Li. H\"olderian error bounds and Kurdyka-{\L}ojasiewicz inequality for the trust region subproblem. Mathematics of Operations Research. 47.4 (2022): 3025-3050. https://doi.org/10.1287/moor.2021.1243 (There is a typo in the first column in Table 1 in the published version, where \perp should be \not\perp.)
  5. Rujun Jiang, Man-Chung Yue, Zhishuo Zhou. An accelerated first-order method with complexity analysis for solving cubic regularization subproblems. Computational Optimization and Applications. 79.2 (2021): 471-506. https://doi.org/10.1007/s10589-021-00274-7
  6. Hezhi Luo, Xiaodong Ding, Jiming Peng, Rujun Jiang and Duan Li. Complexity Results and Effective Algorithms for Worst-case Linear Optimization under Uncertainties. INFORMS Journal on Computing. 33.1 (2020):180-197. https://doi.org/10.1287/ijoc.2019.0941 appendix data and code
  7. Rujun Jiang and Duan Li. A Linear-Time Algorithm for Generalized Trust Region Subproblems. SIAM Journal on Optimization. 30.1 (2020): 915-932.
  8. Rujun Jiang and Duan Li. Second order cone constrained convex relaxations for nonconvex quadratically constrained quadratic programming. Journal of Global Optimization. 75.2 (2019): 461-494. https://doi.org/10.1007/s10898-019-00793-y
  9. Rujun Jiang and Duan Li. Novel reformulations and efficient algorithms for the generalized trust region subproblem. SIAM Journal on Optimization. 29.2 (2019): 1603-1633.
  10. Baiyi Wu, Duan Li and Rujun Jiang. Quadratic Convex Reformulation for Quadratic Programming with Linear On-Off Constraints. European Journal of Operational Research. 274.3 (2019): 824-836.
  11. Xueting Cui, Xiaoling Sun, Shushang Zhu, Rujun Jiang, and Duan Li. Portfolio Optimization with Nonparametric Value at Risk: A Block Coordinate Descent Method. INFORMS Journal on Computing. 30.3 (2018): 454-471. appendix
  12. Rujun Jiang, Duan Li and Baiyi Wu. SOCP reformulation for the generalized trust region subproblem via a canonical form of two symmetric matrices. Mathematical Programming. 169.2 (2018): 531-563.
  13. Rujun Jiang and Duan Li. Simultaneous diagonalization of matrices and its applications in quadratically constrained quadratic programming. SIAM Journal on Optimization. 26.3 (2016): 1649-1668.

Conference Articles

  1. Jiulin Wang, Xu Shi, Rujun Jiang. Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method. To appear in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2024.
  2. He Chen, Haochen Xu, Rujun Jiang, Anthony Man-Cho So. Lower-Level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization. To appear in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2024.
  3. Rufeng Xiao, Yuze Ge, Rujun Jiang and Yifan Yan. Unified Framework for Rank-based Loss Minimization. Advances in Neural Information Processing Systems 36: Proceedings of the 2023 Conference (NeurIPS 2023).
  4. Jiali Wang, Wen Huang, Rujun Jiang, Xudong Li and Alex L. Wang. Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation. International Conference on Machine Learning (ICML), 2022. Outstanding Paper Award code
  5. Jiali Wang, He Chen, Rujun Jiang, Xudong Li and Zihao Li. Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss. International Conference on Machine Learning (ICML), 2021. code
  6. Rujun Jiang, Huikang Liu and Anthony Man-Cho So. LPA-SD: An Efficient First-Order Method for Single-Group Multicast Beamforming. Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2018), 2018.
  7. Rujun Jiang and Duan Li. On Conic Relaxations of Generalization of the Extended Trust Region Subproblem. In World Congress on Global Optimization, pp. 145-154. Springer, Cham, 2019.
  8. Rujun Jiang and Duan Li. Semidefinite Programming Based Convex Relaxation for Nonconvex Quadratically Constrained Quadratic Programming. In World Congress on Global Optimization, pp. 213-220. Springer, Cham, 2019.