| A secure federated transfer learning framework Y Liu, Y Kang, C Xing, T Chen, Q Yang IEEE Intelligent Systems 35 (4), 70-82, 2020 | 570 | 2020 |
| Fedml: A research library and benchmark for federated machine learning C He, S Li, J So, X Zeng, M Zhang, H Wang, X Wang, P Vepakomma, ... arXiv preprint arXiv:2007.13518, 2020 | 371 | 2020 |
| Fedbcd: A communication-efficient collaborative learning framework for distributed features Y Liu, X Zhang, Y Kang, L Li, T Chen, M Hong, Q Yang IEEE Transactions on Signal Processing 70, 4277-4290, 2022 | 203* | 2022 |
| Federated Learning Q Yang, Y Liu, Y Cheng, Y Kang, T Chen, H Yu Synthesis Lectures on Artificial Intelligence and Machine Learning, 2019 | 131* | 2019 |
| Vertical Federated Learning: Concepts, Advances and Challenges Y Liu, Y Kang, T Zou, Y Pu, Y He, X Ye, Y Ouyang, YQ Zhang, Q Yang IEEE Transactions on Knowledge and Data Engineering, 2024 | 100 | 2024 |
| Secure and efficient federated transfer learning S Sharma, C Xing, Y Liu, Y Kang IEEE international conference on big data (Big Data), 2569-2576, 2019 | 94 | 2019 |
| FedCVT: Semi-supervised vertical federated learning with cross-view training Y Kang, Y Liu, X Liang ACM Transactions on Intelligent Systems and Technology 13 (4), 1-16, 2022 | 73 | 2022 |
| FedCG: Leverage conditional gan for protecting privacy and maintaining competitive performance in federated learning Y Wu, Y Kang, J Luo, Y He, Q Yang 2022 International Joint Conference on Artificial Intelligence, 2334-2340, 2022 | 44 | 2022 |
| Privacy-preserving federated adversarial domain adaption over feature groups for interpretability Y Kang, Y Liu, Y Wu, G Ma, Q Yang IEEE Transactions on Big Data, 1 - 12, 2021 | 29 | 2021 |
| Secureboost+: A high performance gradient boosting tree framework for large scale vertical federated learning W Chen, G Ma, T Fan, Y Kang, Q Xu, Q Yang arXiv preprint arXiv:2110.10927, 2021 | 27 | 2021 |
| Trading off privacy, utility and efficiency in federated learning X Zhang, Y Kang, K Chen, L Fan, Q Yang ACM Transactions on Intelligent Systems and Technology, 2022 | 22 | 2022 |
| Defending label inference and backdoor attacks in vertical federated learning Y Liu, Z Yi, Y Kang, Y He, W Liu, T Zou, Q Yang arXiv preprint arXiv:2112.05409 3 (9), 2021 | 21 | 2021 |
| Fate-llm: A industrial grade federated learning framework for large language models T Fan, Y Kang, G Ma, W Chen, W Wei, L Fan, Q Yang arXiv preprint arXiv:2310.10049, 2023 | 20 | 2023 |
| Privacy in large language models: Attacks, defenses and future directions H Li, Y Chen, J Luo, Y Kang, X Zhang, Q Hu, C Chan, Y Song arXiv preprint arXiv:2310.10383, 2023 | 15 | 2023 |
| Federated deep learning with Bayesian privacy H Gu, L Fan, B Li, Y Kang, Y Yao, Q Yang arXiv preprint arXiv:2109.13012, 2021 | 15 | 2021 |
| A framework for evaluating privacy-utility trade-off in vertical federated learning Y Kang, J Luo, Y He, X Zhang, L Fan, Q Yang arXiv preprint arXiv:2209.03885, 2022 | 11 | 2022 |
| Optimizing privacy, utility and efficiency in constrained multi-objective federated learning Y Kang, H Gu, X Tang, Y He, Y Zhang, J He, Y Han, L Fan, Q Yang arXiv preprint arXiv:2305.00312, 2023 | 10 | 2023 |
| A hybrid self-supervised learning framework for vertical federated learning Y He, Y Kang, X Zhao, J Luo, L Fan, Y Han, Q Yang arXiv preprint arXiv:2208.08934, 2022 | 10 | 2022 |
| Batch label inference and replacement attacks in black-boxed vertical federated learning Y Liu, T Zou, Y Kang, W Liu, Y He, Z Yi, Q Yang arXiv preprint arXiv:2112.05409, 2021 | 10 | 2021 |
| FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation H Gu, J Luo, Y Kang, L Fan, Q Yang 2023 International Joint Conference on Artificial Intelligence, 2023 | 7 | 2023 |
Yang (Veronica) LiuAssociate Professor at Tsinghua UniversityVerified email at air.tsinghua.edu.cn
