姜伟   (Wei Jiang) LAMDA Group Department of Computer Science and Technology Nanjing University, Nanjing 210023, China Google Scholar Email: jiangw@lamda.nju.edu.cn

Research Interests

      Machine Learning, Stochastic Optimization.

Education Experiences

• 2020.09 - Now, Ph.D., Computer Science and Technology, Nanjing University.

  • Supervisor: Professor Lijun Zhang
  • 2023.10 - 2024.05, Visiting Student, National University of Singapore.

• 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)

1. 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.
   
   
2. Normalized Adaptive Variance Reduction Method. [PDF]
   W. Jiang, S. Yang, Y. Wang, and L. Zhang
   Journal of Software, to appear, 2025.
   
   
3. 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.
   
   
4. 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.
   
   
5. 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.
   
   
6. 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.
   
   
7. 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.
   
   
8. 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; Information Sciences; Neurocomputing; TMLR.