Preprints

1. Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings. [arXiv]
   W. Jiang, and L. Zhang
   
   
2. Improved Analysis for Sign-based Methods with Momentum Updates. [arXiv]
   W. Jiang, D. Yu, S. Yang, W. Yang, and L. Zhang
   
   
3. Mirror Descent Under Generalized Smoothness [arXiv]
   D. Yu, W. Jiang, Y. Wan, and L. Zhang
   
   
4. Distributed Online Convex Optimization with Efficient Communication: Improved Algorithm and Lower bounds [arXiv]
   S. Yang, W. Yang, W. Jiang, and L. Zhang
   
   
5. Non-Stationary Projection-Free Online Learning with Dynamic Regret Guarantees.
   Y. Wang, H. Bai, W. Jiang, W. Yang, Y. Wan, and L. Zhang
   
   
6. Dual Adaptivity: Universal Algorithms for Minimizing the Adaptive Regret of Convex Functions. [arXiv]
   L. Zhang, W. Yang, G. Wang, W. Jiang, and Z.-H. Zhou
   
   

Journal

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.
   
   

Conference

1. Smoothed Online Convex Optimization with Delayed Feedback [PDF]
   S. Yang, W. Yang, W. Jiang, Y. Wan, and L. Zhang
   In Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025), pages 6812 - 6820, 2025.
   
   
2. 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.
   
   
3. 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.
   
   
4. Online Composite Optimization Between Stochastic and Adversarial Environments [PDF]
   Y. Wang, S. Chen, W. Jiang, W. Yang, Y.Wan and L. Zhang
   In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), pages 94808 - 94850, 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. Small-loss Adaptive Regret for Online Convex Optimization [PDF]
   W. Yang, W. Jiang, Y. Wang, P. Yang, Y. Hu, and L. Zhang
   In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), pages 56156 - 56195, 2024.
   
   
7. Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond [PDF]
   D. Yu, Y. Cai, W. Jiang, and L. Zhang
   In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), pages 57384 - 57414, 2024.
   
   
8. Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees [PDF, arXiv]
   Y. Wang, W. Yang, W. Jiang, S. Lu, B. Wang, H. Tang, Y. Wan, and L. Zhang
   In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024), pages 15671 - 15679, 2024.
   
   
9. Learning Unnormalized Statistical Models via Compositional Optimization [PDF]
   W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, and L. Zhang
   In Proceedings of the 40th International Conference on Machine Learning (ICML 2023), pages 15105 - 15124, 2023.
   
   
10. 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.
    
    
11. Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor [PDF, Supplementary]
    L. Zhang, W. Jiang, J. Yi, and T. Yang
    In Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pages 4928 - 4942, 2022.
    
    
12. 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.
    
    
13. Revisiting Smoothed Online Learning [PDF, Supplementary]
    L. Zhang, W. Jiang, S. Lu, and T. Yang
    In Advances in Neural Information Processing Systems 34 (NeurIPS 2021), pages 13599 - 13612, 2021.
    
    
14. Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions [PDF, Supplementary]
    L. Zhang, G. Wang, W.-W. Tu, W. Jiang, and Z.-H. Zhou
    In Advances in Neural Information Processing Systems 34 (NeurIPS 2021), pages 24968 - 24980, 2021.