| Federated learning via over-the-air computation K Yang, T Jiang, Y Shi, Z Ding IEEE Transactions on Wireless Communications 19 (3), 2022-2035, 2020 | 1039 | 2020 |
| Communication-Efficient Edge AI: Algorithms and Systems Y Shi, K Yang, T Jiang, J Zhang, KB Letaief IEEE Communications Surveys & Tutorials 22 (4), 2167 - 2191, 2020 | 426 | 2020 |
| Federated machine learning for intelligent IoT via reconfigurable intelligent surface K Yang, Y Shi, Y Zhou, Z Yang, L Fu, W Chen IEEE Network 34 (5), 16-22, 2020 | 181 | 2020 |
| A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression K Yang, T Fan, T Chen, Y Shi, Q Yang arXiv preprint arXiv:1912.00513, 2019 | 120 | 2019 |
| Reconfigurable intelligent surface for green edge inference S Hua, Y Zhou, K Yang, Y Shi, K Wang IEEE Transactions on Green Communications and Networking 5 (2), 964-979, 2021 | 72 | 2021 |
| Energy-efficient processing and robust wireless cooperative transmission for edge inference K Yang, Y Shi, W Yu, Z Ding IEEE internet of things journal 7 (10), 9456-9470, 2020 | 53 | 2020 |
| Federated learning based on over-the-air computation K Yang, T Jiang, Y Shi, Z Ding ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 53 | 2019 |
| Data shuffling in wireless distributed computing via low-rank optimization K Yang, Y Shi, Z Ding IEEE transactions on signal processing 67 (12), 3087-3099, 2019 | 46 | 2019 |
| Blind demixing for low-latency communication J Dong, K Yang, Y Shi IEEE Transactions on Wireless Communications 18 (2), 897-911, 2019 | 28 | 2019 |
| Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Vertical Federated Learning X Chen, S Zhou, B Guan, K Yang, H Fao, H Wang, Y Wang 2021 IEEE International Conference on Big Data (Big Data), 1242-1248, 2021 | 24 | 2021 |
| Mobile Edge Artificial Intelligence: Opportunities and Challenges Y Shi, K Yang, Z Yang, Y Zhou Academic Press, 2021 | 21 | 2021 |
| Low-rank matrix completion for mobile edge caching in Fog-RAN via Riemannian optimization K Yang, Y Shi, Z Ding 2016 IEEE Global Communications Conference (GLOBECOM), 1-6, 2016 | 21 | 2016 |
| FedGBF: An efficient vertical federated learning framework via gradient boosting and bagging Y Han, P Du, K Yang arXiv preprint arXiv:2204.00976, 2022 | 14 | 2022 |
| Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost W Xu, H Fan, K Li, K Yang arXiv preprint arXiv:2112.04261, 2021 | 14 | 2021 |
| On-device federated learning via second-order optimization with over-the-air computation S Hua, K Yang, Y Shi 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 1-5, 2019 | 14 | 2019 |
| Generalized low-rank optimization for topological cooperation in ultra-dense networks K Yang, Y Shi, Z Ding IEEE Transactions on Wireless Communications 18 (5), 2539-2552, 2019 | 14 | 2019 |
| Low-rank optimization for data shuffling in wireless distributed computing K Yang, Y Shi, Z Ding 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 9 | 2018 |
| Over-the-Air Computation for Vertical Federated Learning X Zeng, S Xia, K Yang, Y Wu, Y Shi 2022 IEEE International Conference on Communications Workshops (ICC …, 2022 | 6 | 2022 |
| Communication-Efficient Edge AI Inference over Wireless Networks K Yang, Y Zhou, Z Yang, Y Shi arXiv preprint arXiv:2004.13351, 2020 | 5 | 2020 |
| Ranking from crowdsourced pairwise comparisons via smoothed matrix manifold optimization J Dong, K Yang, Y Shi 2017 IEEE International Conference on Data Mining Workshops (ICDMW), 949-956, 2017 | 5 | 2017 |
Yuanming ShiProfessor, ShanghaiTech University在 shanghaitech.edu.cn 的电子邮件经过验证