- 2025 -
Xiaoli Tang, Han Yu & Xiaoxiao Li, "A Reinforcement Learning-based Bidding Strategy for Data Consumers in Auction-based Federated Learning," in Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25), 2025.
Yifei Zhang, Hao Zhu, Junhao Dong, Haoran Shi, Ziqiao Meng, Piotr Koniusz & Han Yu, "CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning," in Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25), 2025.
Zhuang Qi, Yu Pan, Lei Meng, Sijin Zhou, Han Yu, Xiaoxiao Li & Xiangxu Meng, "Global Prompt Refinement with Non-Interfering Attention Masking for One-Shot Federated Learning," in Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25), 2025.
Liping Yi, Han Yu, Gang Wang, Xiaoguang Liu & Xiaoxiao Li, "Federated Representation Angle Learning," in Proceedings of the 2025 International Conference on Computer Vision (ICCV'25), 2025.
Zhuang Qi, Sijin Zhou, Lei Meng, Han Hu, Han Yu & Xiangxu Meng, "Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization," in Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI'25), 2025.
Xiaoli Tang, Han Yu, Zengxiang Li & Xiaoxiao Li, "Multi-Session Budget Optimization for Forward Auction-based Federated Learning," in Proceedings of the 42nd International Conference on Machine Learning (ICML'25), 2025.
Yifei Zhang, Hao Zhu, Alysa Ziying Tan, Dianzhi Yu, Longtao Huang & Han Yu, "pFedMixF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation," in Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'25), 2025.
Liping Yi, Han Yu, Gang Wang, Xiaoguang Liu & Xiaoxiao Li, "pFedAFM: Adaptive Feature Mixture for Data-Level Personalization in Heterogeneous Federated Learning on Mobile Edge Devices," in Proceedings of the 41st IEEE International Conference on Data Engineering (ICDE'25), 2025.
Xiaoli Tang & Han Yu, "Reputation-aware Revenue Allocation for Auction-based Federated Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
Liping Yi, Han Yu, Chao Ren, Gang Wang, Xiaoguang Liu & Xiaoxiao Li, "pFedES: Generalized Proxy Feature Extractor Sharing for Model Heterogeneous Personalized Federated Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
Xianjie Guo, Kui Yu, Lizhen Cui, Han Yu & Xiaoxiao Li, "Federated Causally Invariant Feature Learning," in Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
- 2024 -
Liping Yi, Han Yu, Chao Ren, Gang Wang, Xiaoguang Liu & Xiaoxiao Li, "Federated Model Heterogeneous Matryoshka Representation Learning," in Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24), 2024.
Xiaoli Tang & Han Yu. Fairness-aware reverse auction-based federated learning. IEEE Internet of Things Journal, IEEE (2024). (IF: 8.2)
Xiaoli Tang & Han Yu. A cost-aware utility-maximizing bidding strategy for auction-based federated learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2024). (IF: 10.2)
Xiaoli Tang, Han Yu, Run Tang, Chao Ren, Anran Li & Xiaoxiao Li, "Dual Calibration-based Personalised Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), 2024.
Hongyi Peng, Han Yu, Xiaoli Tang & Xiaoxiao Li, "FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler," in Proceedings of the 41st International Conference on Machine Learning (ICML'24), 2024.