… FEDERATED LEARNING SYSTEMS In this section, we first introduce the general learning
prob… For the client-edge-cloud hierarchical FL system, we present the proposed three-layer FL …

… We show that this hierarchical federated learning (HFL) scheme significantly reduces the …
To this end we propose the hierarchical FL framework, where MUs are clustered according to …

… As such, we propose a federated learning with hierarchical clustering (FL+HC) setting.
During the FL procedure, a clustering step at communication round n is introduced. At the …

… is the privacy preserving machine learning paradigm known as Federated Learning (FL), which
… To reduce node failures and device dropouts, the Hierarchical Federated Learning (HFL) …

Federated learning (FL) is promising in enabling large-scale model training by massive …
Fueled by this issue, we consider a hierarchical FL system and formulate a joint problem of edge …

Federated learning (FL) is a powerful distributed machine learning framework where a server
aggregates models trained by … Hierarchical FL, with a client-edge-cloud aggregation …

Federated Learning (FL) is a promising privacy-preserving distributed machine learning
paradigm. However, communication inefficiency remains the key bottleneck that impedes its …

… In this paper, we have designed a cluster-based federated learning mechanism with hierarchical
… that our proposed mechanism will provide a valuable solution for federated learning. …

… To fill this gap, in this paper, we propose a heterogeneous federated learning approach
to train machine learning models over heterogeneous EEG data, while preserving the data …

… We propose a hierarchical federated learning optimization framework over wireless edge
networks to study the problem of participant cost minimization in the worst case. …