Fair selection of edge nodes to participate in clustered federated multitask learning
Clustered federated Multitask learning is introduced as an efficient technique when data is
unbalanced and distributed amongst clients in a non-independent and identically distributed …
unbalanced and distributed amongst clients in a non-independent and identically distributed …
FedAGL: A Communication-Efficient Federated Vehicular Network
With the development of the technologies deployed on vehicles, there is a significant
increase in the amount of data, which comes from various applications, such as battery …
increase in the amount of data, which comes from various applications, such as battery …
Optimized Power Control for Privacy-Preserving Over-the-Air Federated Edge Learning With Device Sampling
Over-the-air federated edge learning (Air-FEEL) shows promise as a distributed machine
learning paradigm for edge devices. By leveraging the superposition property of a multiple …
learning paradigm for edge devices. By leveraging the superposition property of a multiple …
Balanced energy consumption based on historical participation of resource-constrained devices in federated edge learning
In recent years, Federated Edge Learning has gained interest from both industry and
academia for deployment at the wireless network edge. However, some resource-restricted …
academia for deployment at the wireless network edge. However, some resource-restricted …