jiangwei.jpg 



姜伟   教授
计算机科学与工程学院
南京理工大学
邮箱: jiangw@lamda.nju.edu.cn;   12025220@njust.edu.cn
[英文版]


研究方向

      机器学习, 随机优化, 大模型优化.

工作经历

教育经历

代表论文 (所有论文列表)

  1. Optimizing Unnormalized Statistical Models through Compositional Optimization [PDF]
    W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, and L. Zhang
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 48(2): 1949 - 1960, 2026.

  2. 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.

  3. Normalized Adaptive Variance Reduction Method [PDF]
    W. Jiang, S. Yang, Y. Wang, and L. Zhang
    Journal of Software, 36(11): 4893 - 4905, 2025.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

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.

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