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Peichun Li
Peichun Li
University of Macau, Guangdong University of Technology
在 um.edu.mo 的电子邮件经过验证
标题
引用次数
引用次数
年份
Toward resource-efficient federated learning in mobile edge computing
R Yu, P Li
IEEE Network 35 (1), 148-155, 2021
862021
Fedparking: A federated learning based parking space estimation with parked vehicle assisted edge computing
X Huang, P Li, R Yu, Y Wu, K Xie, S Xie
IEEE Transactions on Vehicular Technology 70 (9), 9355-9368, 2021
492021
Social welfare maximization in container-based task scheduling for parked vehicle edge computing
X Huang, P Li, R Yu
IEEE Communications Letters 23 (8), 1347-1351, 2019
262019
FedGreen: Federated learning with fine-grained gradient compression for green mobile edge computing
P Li, X Huang, M Pan, R Yu
2021 IEEE Global Communications Conference (GLOBECOM), 1-6, 2021
52021
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices
P Li, G Cheng, X Huang, J Kang, R Yu, Y Wu, M Pan
IEEE INFOCOM'23, 2023
12023
FedRelay: Federated Relay Learning for 6G Mobile Edge Intelligence
P Li, Y Zhong, C Zhang, Y Wu, R Yu
IEEE Transactions on Vehicular Technology, 2022
12022
A Survey on Integrated Sensing, Communication, and Computing Networks for Smart Oceans
M Dai, Y Li, P Li, Y Wu, L Qian, B Lin, Z Su
Journal of Sensor and Actuator Networks 11 (4), 70, 2022
12022
Split Learning with Differential Privacy for Integrated Terrestrial and Non-Terrestrial Networks
M Wu, G Cheng, P Li, R Yu, Y Wu, M Pan, R Lu
IEEE Wireless Communications, 2023
2023
FAST: Fidelity-Adjustable Semantic Transmission over Heterogeneous Wireless Networks
P Li, G Cheng, J Kang, R Yu, L Qian, Y Wu, D Niyato
arXiv preprint arXiv:2304.01857, 2023
2023
Snowball: Energy Efficient and Accurate Federated Learning with Coarse-to-Fine Compression over Heterogeneous Wireless Edge Devices
P Li, G Cheng, X Huang, J Kang, R Yu, Y Wu, M Pan, D Niyato
IEEE Transactions on Wireless Communications, 2023
2023
Privacy-preserving incentive mechanism for platoon assisted vehicular edge computing with deep reinforcement learning
X Huang, Y Zhong, Y Wu, P Li, R Yu
China Communications 19 (7), 294-309, 2022
2022
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