| Sample-level data selection for federated learning A Li, L Zhang, J Tan, Y Qin, J Wang, XY Li IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021 | 134 | 2021 |
| Federated graph neural networks: Overview, techniques, and challenges R Liu, P Xing, Z Deng, A Li, C Guan, H Yu IEEE Transactions on Neural Networks and Learning Systems, 2024 | 116 | 2024 |
| Privacy-preserving efficient federated-learning model debugging A Li, L Zhang, J Wang, F Han, XY Li IEEE Transactions on Parallel and Distributed Systems 33 (10), 2291-2303, 2021 | 49 | 2021 |
| Efficient federated-learning model debugging A Li, L Zhang, J Wang, J Tan, F Han, Y Qin, NM Freris, XY Li 2021 IEEE 37th International Conference on Data Engineering (ICDE), 372-383, 2021 | 42 | 2021 |
| FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning A Li, H Peng, L Zhang, J Huang, Q Guo, H Yu, Y Liu IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 37 | 2023 |
| Efficient participant contribution evaluation for horizontal and vertical federated learning J Wang, L Zhang, A Li, X You, H Cheng 2022 IEEE 38th International Conference on Data Engineering (ICDE), 911-923, 2022 | 31 | 2022 |
| Appdna: App behavior profiling via graph-based deep learning S Xue, L Zhang, A Li, XY Li, C Ruan, W Huang IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 1475-1483, 2018 | 21 | 2018 |
| TODQA: Efficient task-oriented data quality assessment A Li, L Zhang, J Qian, X Xiao, XY Li, Y Xie 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN …, 2019 | 19 | 2019 |
| An Empirical Study of Automated Vulnerability Localization with Large Language Models J Zhang, C Wang, A Li, W Sun, C Zhang, W Ma, Y Liu arXiv preprint arXiv:2404.00287, 2024 | 18 | 2024 |
| Residue-based label protection mechanisms in vertical logistic regression J Tan, L Zhang, Y Liu, A Li, Y Wu 2022 8th International Conference on Big Data Computing and Communications …, 2022 | 17 | 2022 |
| Federated iot interaction vulnerability analysis G Wang, H Guo, A Li, X Liu, Q Yan 2023 IEEE 39th International Conference on Data Engineering (ICDE), 1517-1530, 2023 | 15 | 2023 |
| Towards interpretable federated learning A Li, R Liu, M Hu, LA Tuan, H Yu arXiv preprint arXiv:2302.13473, 2023 | 15 | 2023 |
| FedMut: Generalized Federated Learning via Stochastic Mutation M Hu, Y Cao, A Li, Z Li, C Liu, T Li, M Chen, Y Liu Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12528 …, 2024 | 14 | 2024 |
| FedCross: Towards accurate federated learning via multi-model cross-aggregation M Hu, P Zhou, Z Yue, Z Ling, Y Huang, A Li, Y Liu, X Lian, M Chen 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2137-2150, 2024 | 13 | 2024 |
| Subnetwork-lossless robust watermarking for hostile theft attacks in deep transfer learning models J Jia, Y Wu, A Li, S Ma, Y Liu IEEE transactions on dependable and secure computing, 2022 | 13 | 2022 |
| Efficient and privacy-preserving feature importance-based vertical federated learning A Li, J Huang, J Jia, H Peng, L Zhang, LA Tuan, H Yu, XY Li IEEE Transactions on Mobile Computing, 2023 | 11 | 2023 |
| Aggregating intrinsic information to enhance BCI performance through federated learning R Liu, Y Chen, A Li, Y Ding, H Yu, C Guan Neural Networks 172, 106100, 2024 | 10 | 2024 |
| GFL: Federated learning on non-IID data via privacy-preserving synthetic data Y Cheng, L Zhang, A Li 2023 IEEE International Conference on Pervasive Computing and Communications …, 2023 | 10 | 2023 |
| Advances and open challenges in federated learning with foundation models C Ren, H Yu, H Peng, X Tang, A Li, Y Gao, A Ziying Tan, B Zhao, X Li, Z Li, ... arXiv e-prints, arXiv: 2404.15381, 2024 | 8 | 2024 |
| Fairness via Group Contribution Matching. T Li, Z Li, A Li, M Du, A Liu, Q Guo, G Meng, Y Liu IJCAI, 436-445, 2023 | 8 | 2023 |
Han YuAssociate Professor, CCDS, Nanyang Technological University, SingaporeZweryfikowany adres z ntu.edu.sg