| FedLab: A Flexible Federated Learning Framework D Zeng, S Liang, X Hu, H Wang, Z Xu Journal of Machine Learning Research 24 (100), 1-7, 2023 | 99 | 2023 |
| A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy Y Zhang, D Zeng, J Luo, Z Xu, I King Companion Proceedings of the ACM Web Conference 2023, 1167-1176, 2023 | 45* | 2023 |
| Stochastic Clustered Federated Learning D Zeng, X Hu, S Liu, Y Yu, Q Wang, Z Xu KDD FL4Data-Mining Workshop, 2023., 2023 | 15 | 2023 |
| On Diversified Preferences of Large Language Model Alignment D Zeng, Y Dai, P Cheng, L Wang, T Hu, W Chen, N Du, Z Xu Findings of the Association for Computational Linguistics: EMNLP 2024, 9194-9210, 2024 | 10* | 2024 |
| On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond D Zeng, Z Xu, Y Pan, Q Wang, X Tang arXiv preprint arXiv:2310.02702, 2023 | 7* | 2023 |
| FedNoisy: Federated Noisy Label Learning Benchmark S Liang, J Huang, J Hong, D Zeng, J Zhou, Z Xu arXiv preprint arXiv:2306.11650, 2023 | 5 | 2023 |
| Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization M Wang, D Zeng, Z Xu, R Guo, X Zhao 2023 IEEE International Conference on Data Mining (ICDM), 1361-1366, 2023 | 4 | 2023 |
| Flexible Contribution Estimation Methods for Horizontal Federated Learning X Hu, C Luo, D Zeng, Z Xu, P Guo, I King 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 4 | 2023 |
| Topology Learning for Heterogeneous Decentralized Federated Learning Over Unreliable D2D Networks Z Wu, Z Xu, D Zeng, J Li, J Liu IEEE Transactions on Vehicular Technology, 2024 | 3 | 2024 |
| Federated Generalization via Information-theoretic Distribution Diversification Z Wu, Z Xu, D Zeng, Q Wang arXiv preprint arXiv:2310.07171, 2023 | 3 | 2023 |
| Encoded Gradients Aggregation against Gradient Leakage in Federated Learning D Zeng, S Liu, S Liang, Z Li, H Wang, I King, Z Xu arXiv preprint arXiv:2205.13216, 2022 | 2* | 2022 |
| Personalized Federated Learning via Amortized Bayesian Meta-Learning S Liu, S Lv, D Zeng, Z Xu, H Wang, Y Yu arXiv preprint arXiv:2307.02222, 2023 | 1 | 2023 |
| Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization D Zeng, Z Wu, S Liu, Y Pan, X Tang, Z Xu arXiv preprint arXiv:2411.16303, 2024 | | 2024 |
| FedCVD: The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data Y Zhang, G Chen, Z Xu, J Wang, D Zeng, J Li, J Wang, Y Qi, I King arXiv preprint arXiv:2411.07050, 2024 | | 2024 |
| Enhanced Federated Optimization: Adaptive Unbiased Client Sampling with Reduced Variance D Zeng, Z Xu, Y Pan, X Luo, Q Wang, X Tang arXiv preprint arXiv:2310.02698, 2023 | | 2023 |
Zenglin XuFudan UniversityVerified email at fudan.edu.cn
Zenglin XuFudan UniversityVerified email at fudan.edu.cn