研究方向
机器学习, 随机优化.
工作经历
教育经历
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2020.09 - 2025.06, 博士, 计算机科学与技术, 南京大学.
- 2023.10 - 2024.05, 联合培养博士研究生, 新加坡国立大学.
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2016.09 - 2020.06, 学士, 计算机科学与技术(实验班), 西安交通大学.
- 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.
奖励与荣誉
- 南京大学优秀毕业生, 2025
- 博士研究生国家奖学金, 2024
- 南京大学优秀研究生标兵, 2024
- NeurIPS优秀审稿人, 2024
- 博士研究生国家奖学金, 2023
- 南京大学优秀研究生标兵, 2023
- LAMDA英才奖, 2023
- 腾讯奖学金, 2022
- 南京大学优秀研究生, 2022
- 兴业银行奖学金, 2021
- 南京大学优秀研究生, 2021
- DeeCamp人工智能训练营总冠军 (奖金10万元)
- 西安交通大学优秀毕业生, 2020
项目
复合损失函数的分布式学习.
江苏省研究生科研创新计划 (KYCX24_0231), 2024.05-2025.05.
学术服务
- 会议审稿人: ICML 2025,2024,2023,2022; NeurIPS 2024,2023,2022; ICLR 2025,2024; AAAI 2025; AISTATS 2023.
- 期刊审稿人: IEEE Transactions on Information Forensics & Security; IEEE Transactions on Evolutionary Computation; Machine Learning; Applied Numerical Mathematics; Information Sciences; Neurocomputing; TMLR.