| Federated-learning-enabled intelligent fog radio access networks: Fundamental theory, key techniques, and future trends Z Zhao, C Feng, HH Yang, X Luo IEEE wireless communications 27 (2), 22-28, 2020 | 128 | 2020 |
| Federated learning with non-IID data in wireless networks Z Zhao, C Feng, W Hong, J Jiang, C Jia, TQS Quek, M Peng IEEE Transactions on Wireless communications 21 (3), 1927-1942, 2021 | 115 | 2021 |
| Mobility-aware cluster federated learning in hierarchical wireless networks C Feng, HH Yang, D Hu, Z Zhao, TQS Quek, G Min IEEE Transactions on Wireless Communications 21 (10), 8441-8458, 2022 | 93 | 2022 |
| On the design of federated learning in the mobile edge computing systems C Feng, Z Zhao, Y Wang, TQS Quek, M Peng IEEE Transactions on Communications 69 (9), 5902-5916, 2021 | 49 | 2021 |
| EdgeGO: A mobile resource-sharing framework for 6G edge computing in massive IoT systems R Cong, Z Zhao, G Min, C Feng, Y Jiang IEEE Internet of Things Journal 9 (16), 14521-14529, 2021 | 49 | 2021 |
| Attention-based graph convolutional network for recommendation system C Feng, Z Liu, S Lin, TQS Quek ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 43 | 2019 |
| Joint optimization of data sampling and user selection for federated learning in the mobile edge computing systems C Feng, Y Wang, Z Zhao, TQS Quek, M Peng 2020 IEEE International Conference on Communications Workshops (ICC …, 2020 | 35 | 2020 |
| Proactive content caching scheme in urban vehicular networks B Feng, C Feng, D Feng, Y Wu, XG Xia IEEE Transactions on Communications 71 (7), 4165-4180, 2023 | 16 | 2023 |
| Hybrid Learning: When Centralized Learning Meets Federated Learning in the Mobile Edge Computing Systems C Feng, HH Yang, S Wang, Z Zhao, TQS Quek IEEE Transactions on Communications, 2023 | 14 | 2023 |
| Semi-synchronous personalized federated learning over mobile edge networks C You, D Feng, K Guo, HH Yang, C Feng, TQS Quek IEEE Transactions on Wireless Communications 22 (4), 2262-2277, 2022 | 12 | 2022 |
| Privacy-preserving federated learning based on differential privacy and momentum gradient descent S Weng, L Zhang, D Feng, C Feng, R Wang, PV Klaine, MA Imran 2022 International Joint Conference on Neural Networks (IJCNN), 1-6, 2022 | 11 | 2022 |
| Privacy-preserving hierarchical federated recommendation systems Y Chen, C Feng, D Feng IEEE Communications Letters 27 (5), 1312-1316, 2023 | 10 | 2023 |
| Federated learning with user mobility in hierarchical wireless networks C Feng, HH Yang, D Hu, TQS Quek, Z Zhao, G Min 2021 IEEE Global Communications Conference (GLOBECOM), 01-06, 2021 | 6 | 2021 |
| Foundation model based native AI framework in 6G with cloud-edge-end collaboration X Chen, Z Guo, X Wang, HH Yang, C Feng, J Su, S Zheng, TQS Quek arXiv preprint arXiv:2310.17471, 2023 | 5 | 2023 |
| On the convergence rate of federated learning over unreliable networks C Feng, HH Yang, Z Chen, D Feng, Z Wang, TQS Quek 2021 Computing, Communications and IoT Applications (ComComAp), 59-64, 2021 | 4 | 2021 |
| Power control in full duplex networks: Area spectrum efficiency and energy efficency C Feng, Y Zhong, TQS Quek, G Wu 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 4 | 2017 |
| Large language models for base station siting: Intelligent deployment based on prompt or agent Y Wang, MM Afzal, Z Li, J Zhou, C Feng, S Guo, TQS Quek arXiv preprint arXiv:2408.03631, 2024 | 3 | 2024 |
| EAPS: Edge-assisted privacy-preserving federated prediction systems D Feng, G Huang, C Feng, B Cao, Z Wang, XG Xia 2023 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, 2023 | 3 | 2023 |
| Trustworthy Image Semantic Communication with GenAI: Explainablity, Controllability, and Efficiency X Wang, D Ye, C Feng, HH Yang, X Chen, TQS Quek arXiv preprint arXiv:2408.03806, 2024 | 2 | 2024 |
| Robust Privacy-Preserving Recommendation Systems Driven by Multimodal Federated Learning C Feng, D Feng, G Huang, Z Liu, Z Wang, XG Xia IEEE Transactions on Neural Networks and Learning Systems, 2024 | 2 | 2024 |
Tony Q.S. QuekFull Professor and ISTD Pillar Head, SUTD在 ieee.org 的电子邮件经过验证
