Federated continual learning via knowledge fusion: A survey X Yang, H Yu, X Gao, H Wang, J Zhang, T Li IEEE Transactions on Knowledge and Data Engineering, 2024 | 35 | 2024 |
Personalized federated continual learning via multi-granularity prompt H Yu, X Yang, X Gao, Y Kang, H Wang, J Zhang, T Li Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 6 | 2024 |
FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer X Gao, X Yang, H Yu, Y Kang, T Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 3 | 2024 |
Overcoming Spatial-Temporal Catastrophic Forgetting for Federated Class-Incremental Learning H Yu, X Yang, X Gao, Y Feng, H Wang, Y Kang, T Li Proceedings of the 32nd ACM International Conference on Multimedia, 5280-5288, 2024 | 2 | 2024 |
A New Perspective on Privacy Protection in Federated Learning with Granular-Ball Computing G Lai, Y Feng, X Yang, X Deng, H Yu, S Xia, G Wang, T Li arXiv preprint arXiv:2501.04940, 2025 | | 2025 |
Addressing Spatial-Temporal Data Heterogeneity in Federated Continual Learning via Tail Anchor H Yu, X Yang, L Zhang, H Gu, T Li, L Fan, Q Yang arXiv preprint arXiv:2412.18355, 2024 | | 2024 |