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Research Interests
Machine Learning, Stochastic Optimization.
Working Experiences
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2025.10 - now, Nanjing University of Science and Technology.
- Professor, School of Computer Science and Engineering.
Education Experiences
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2020.09 - 2025.06, Ph.D., Computer Science and Technology, Nanjing University.
- Supervisor: Professor Lijun Zhang (LAMDA Group).
- 2023.10 - 2024.05, Visiting Student, National University of Singapore.
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2016.09 - 2020.06, B.E., Computer Science and Technology (Honors Science Program), Xi'an Jiaotong University.
- 2019.01 - 2019.06, Exchange Student, University of California, Berkeley. [certificate][transcript]
- 2018.07 - 2018.08, Exchange Student, University of Manchester. [certificate]
Selected Papers (Publications by Year)
- Optimizing Unnormalized Statistical Models through Compositional Optimization
W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, and L. Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), to appear, 2025.
- Revisiting Stochastic Multi-Level Compositional Optimization [PDF]
W. Jiang, S. Yang, Y. Wang, T. Yang, and L. Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 47(7): 5613 - 5624, 2025.
- Normalized Adaptive Variance Reduction Method [PDF]
W. Jiang, S. Yang, Y. Wang, and L. Zhang
Journal of Software, 36(11): 4893 - 4905, 2025.
- Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions [PDF]
W. Jiang, S. Yang, Y. Wang, and L. Zhang
In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), pages 22047 - 22080, 2024.
- Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction [PDF]
W. Jiang, S. Yang, W. Yang, and L. Zhang
In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), pages 33891 - 33932, 2024.
- Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization [PDF]
W. Jiang, S. Yang, W. Yang, Y. Wang, Y. Wan, and L. Zhang
In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), pages 21962 - 21987, 2024.
- Learning Unnormalized Statistical Models via Compositional Optimization [PDF]
W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, L. Zhang
In Proceedings of the 40th International Conference on Machine Learning (ICML 2023), pages 15105 - 15124, 2023.
- Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization [PDF, Supplementary]
W. Jiang, G. Li, Y. Wang, L. Zhang, and T. Yang
In Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pages 32499 - 32511, 2022.
- Optimal Algorithms for Stochastic Multi-Level Compositional Optimization [PDF]
W. Jiang, B. Wang, Y. Wang, L. Zhang, and T. Yang
In Proceedings of the 39th International Conference on Machine Learning (ICML 2022), pages 10195 - 10216, 2022.
Honors and Awards
- Excellent Graduate of Nanjing University, 2025
- National Scholarship, 2024
- Excellent Student of Nanjing University, 2024
- NeurIPS Top Reviewer, 2024
- National Scholarship, 2023
- Excellent Student of Nanjing University, 2023
- LAMDA Elite Award, 2023
- Tencent Scholarship, 2022
- Excellent Student of Nanjing University, 2022
- Industrial Bank Scholarship, 2021
- Excellent Student of Nanjing University, 2021
- Grand Champion of DeeCamp Artificial Intelligence Camp, 2020 (￥100,000)
- Excellent Graduate of Xi'an jiaotong University, 2020
Foundation
Distributed Optimization of Compositional Loss Functions. Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX24_0231) 2024.05-2025.05
Academic Service
- Reviewer for Conferences: ICML 2025,2024,2023,2022; NeurIPS 2024,2023,2022; ICLR 2025,2024; AAAI 2025; AISTATS 2023.
- Reviewer for Journal: IEEE Transactions on Information Forensics & Security; IEEE Transactions on Evolutionary Computation; Machine Learning; Applied Numerical Mathematics; Information Sciences; Neurocomputing; TMLR.