… Federated Learning, the … of Federated Learning for distributed Edge–Fog–Cloud architecture
in the IoT smart healthcare sector. This paper presents FedSDM, the Federated Learning-…

… federated learning in edge/cloud computing environments. 3) ChainFL can be deployed as
a federated learning … devices to enable federated learning in edge computing environments. …

… extension of cloud computing. Edge computing combined with cloud computing has three
… We analyzed the implementation of federated learning in an edge computing environment …

… In such cases, the offloading of the data-sets in cloud computing to bring out the efficient
Machine-learning solutions, but this would not show the feasibility because of privacy constraints…

… research directions of federated learning. Finally, we summarize the characteristics of
existing federated learning, and analyze the current practical application of federated learning. …

… Federated Adaptive Training), to effectively cope with systems and statistical heterogeneity in
mobile edge computing environment… number of local training iterations to clients to achieve …

… of federated learning leveraging edge computing, as embodied by our DPMN algorithm,
presents a promising approach to improving recommendation systems within cloud computing …

… federated learning method to solve this problem. This method allows edge nodes to select
part of the model from the cloud … efficiency of federated learning. Compared with the original …

… Federated Learning (FL) is emerging as a promising technology to build machine
learning models in a decentralized, privacy-preserving fashion. Indeed, FL enables local …

… machine learning. So far, we propose an architecture for federated learning services … A
federation of cognitive cloud services for trusting data sources. In: Conference on Complex…