… suitable for edge network machine learning scenarios where the … federated learning
mechanism for edge network computing (EAFLM), which compresses the redundant communication …

… Federated learning (FL)mitigates data sharing issues through local training,yet the large …
and communication bandwidth,making deployment in edge networks difficult. Considering split …

… in complex networks, we study the communication efficiency optimization methods of …
federated learning in mobile edge networks. IEEE/CIC Int Conf on Communications in China, p.1-6. …

… , reduces communication delay, improves the accuracy of joint … Federated learning for
internet of things: Recent advances, taxonomy, and open challenges[J]. IEEE Communications …

… Abstract: In order to optimize the training delay of the hierarchical Federated Learning (FL) …
terminal devices and edge servers and the minimum edge model training delay are obtained. …

… , and the cloud performs edge server model aggregation and … the communication overhead
during federated learning … redundant communication between the device end and the edge …

… at the problems of unbalanced edge device resources, communication delay and low model
… an adaptive federated learning algorithm for environmental monitoring based on edge …

… 基于上述考虑,本文提出一种基于联邦学习 (FL, federated learning)的分布式边缘计算模型,并
将其应用于视频监控系统,该方法仅传输神经网络 模型权重,免于视频数据的传输.经实验发现,本 文…

… of graph theory, game theory, machine learning, federated learning and other theories, the
… mobile edge networks: architecture, challenges, and opportunities[J]. IEEE Communications …

… discussed from the aspects of security, mobility-aware caching, edge caching based on
reinforcement learning and federated learning and edge caching for Beyond 5G/6G networks. …