… network parameter configuration optimization at the network level. Therefore, deploying FL in
6G will also face the problem of generalization and adaptability… federated learning networks…

… Despite intensive research on federated learning, existing … The problem of designing a secure
federated learning … , a verifiable and auditable federated learning framework based on the …

… and networking resources of the participants delay the training and aggregation. The paper
introduces a novel approach to federated learning by … It enables adaptability to the varying …

… hierarchical structure of neural networks and introduces layer-… Fisher Information to enhance
the adaptability of the model to … assessment of our method’s robustness and adaptability. …

… Our method is readily adaptable, free of computation overhead, and only rely on the single
… Dropout: a simple way to prevent neural networks from overfitting. The journal of machine …

… We develop hierarchical nested personalized federated learning (HN-PFL), which exploits
meta-gradient based learning across disconnected device clusters and yield personalized …

… , especially in consideration of its virtue of strong adaptability [8]. Intelligent IoT or AIoT (…
Himayat, “Coded computing for low-latency federated learning over wireless edge networks,…

… Virtually, federated learning was initially designed to make … , the network bandwidth of the
clients in federated learning is … and hardware condition, which proved the adaptability of the …

… customization by learning a set of base sub-networks of … • Within the domain of heterogeneous
federated learning, we … only efficient in federated communication and flexibly adaptable to …

… , they did not discuss the datasets used for implementation of federated learning in edge
networks. … For mitigating the issues, the FL technique provides an adaptable platform to the data …