| Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and Trends in Machine Learning (FnTML) 14 (1–2), 1–210, 2021 | 6468 | 2021 |
| Towards personalized federated learning AZ Tan, H Yu, L Cui, Q Yang IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 34 (12 …, 2023 | 942 | 2023 |
| A survey of zero-shot learning: Settings, methods and applications W Wang, VW Zheng, H Yu, C Miao ACM Transactions on Intelligent Systems and Technology (TIST) 10 (2), 13:1–13:19, 2019 | 729 | 2019 |
| Visual Domain Adaptation with Manifold Embedded Distribution Alignment J Wang, W Feng, Y Chen, H Yu, M Huang, PS Yu The 26th ACM International Conference on Multimedia (ACM MM'18), 402–410, 2018 | 679 | 2018 |
| Threats to federated learning L Lyu, H Yu, J Zhao, Q Yang Federated Learning: Privacy and Incentive, 3-16, 2020 | 657* | 2020 |
| Privacy and robustness in federated learning: Attacks and defenses L Lyu, H Yu, X Ma, C Chen, L Sun, J Zhao, Q Yang, PS Yu IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 35 (7 …, 2024 | 399 | 2024 |
| A survey of trust and reputation management systems in wireless communications H Yu, Z Shen, C Miao, C Leung, D Niyato Proceedings of the IEEE 98 (10), 1755–1772, 2010 | 358 | 2010 |
| FedVision: An Online Visual Object Detection Platform Powered by Federated Learning Y Liu, A Huang, Y Luo, H Huang, Y Liu, Y Chen, L Feng, T Chen, H Yu, ... The 32nd Annual Conference on Innovative Applications of AI (IAAI-20), 13172 …, 2020 | 340 | 2020 |
| Building Ethics into Artificial Intelligence H Yu, Z Shen, C Miao, C Leung, VR Lesser, Q Yang The 27th International Joint Conference on Artificial Intelligence (IJCAI'18 …, 2018 | 300 | 2018 |
| Transfer learning with dynamic distribution adaptation J Wang, Y Chen, W Feng, H Yu, M Huang, Q Yang ACM Transactions on Intelligent Systems and Technology (TIST) 11 (1), 6:1–6:25, 2020 | 280 | 2020 |
| Incentive design for efficient federated learning in mobile networks: A contract theory approach J Kang, Z Xiong, D Niyato, H Yu, YC Liang, DI Kim 2019 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS), 1–5, 2019 | 278 | 2019 |
| A survey of multi-agent trust management systems H Yu, Z Shen, C Leung, C Miao, VR Lesser IEEE Access 1 (1), 35–50, 2013 | 274 | 2013 |
| Towards fair and privacy-preserving federated deep models L Lyu, J Yu, K Nandakumar, Y Li, X Ma, J Jin, H Yu, KS Ng IEEE Transactions on Parallel and Distributed Systems (TPDS) 31 (11), 2524–2541, 2020 | 271 | 2020 |
| A Fairness-aware Incentive Scheme for Federated Learning H Yu, Z Liu, Y Liu, T Chen, M Cong, X Weng, D Niyato, Q Yang The 3rd AAAI/ACM Conference on AI, Ethics, and Society (AIES-20), 393–399, 2020 | 269 | 2020 |
| Collaborative fairness in federated learning L Lyu, X Xu, Q Wang, H Yu Federated Learning: Privacy and Incentive, 189-204, 2020 | 225 | 2020 |
| A study on factors affecting service quality and loyalty intention in mobile banking Q Zhou, FJ Lim, H Yu, G Xu, X Ren, D Liu, X Wang, X Mai, H Xu Journal of Retailing and Consumer Services (JRCS) 60 (102424), doi:10.1016/j …, 2021 | 207 | 2021 |
| Deep Model for Dropout Prediction in MOOCs W Wang, H Yu, C Miao The 2nd International Conference on Crowd Science and Engineering (ICCSE'17 …, 2017 | 192 | 2017 |
| Easy Transfer Learning by Exploiting Intra-domain Structures J Wang, Y Chen, H Yu, M Huang, Q Yang The 2019 IEEE International Conference on Multimedia and Expo (ICME'19 …, 2019 | 179 | 2019 |
| Federated Learning Q Yang, Y Liu, Y Cheng, Y Kang, T Chen, H Yu Springer, Cham, 2020 | 167* | 2020 |
| Towards fairness-aware federated learning Y Shi, H Yu, C Leung. IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 35 (9 …, 2024 | 139* | 2024 |
Chunyan MiaoNanyang Technological Universityntu.edu.sg의 이메일 확인됨