… In Section 3, we present a selection of existing surveys on Federated Learning. Section 4
provides an overview of FL and a comprehensive examination of its methodologies and …

… [53] proposed the use of federated learning for 6G networks. Federated learning is able to …
models and collaborative learning are needed for federated learning among the devices. The …

… To mitigate privacy concerns associated with centralized approaches, in recent years the
use of Federated Learning (FL) has attracted a significant interest in different sectors, including …

… a recent review of federated learning in the medical domain. … To fill the gap, this review
presents a survey of FL from the … survey, we review the current progress on federated learning …

… Nowadays smart machines and smart factories use machine learning/deep learning based
… In order to address this issue, federated learning (FL) technology is implemented in IIoT by …

… federated learning algorithms' learning performance is challenging to model. This work
examines the design of a federated learning … of existing federated learning incentive mechanisms…

… several surveys on FL and IoUT separately, there is no survey on FL for IoUT to the best of
our knowledge, which is a motivating factor for this survey. … Federated Learning FL is a recent …

… We describe how distillation is used in federated learning using FedMD: In addition to the
devices’ local (private) datasets, a second dataset Dp is introduced, which is a public dataset …

… Federated learning (FL) has emerged as a new paradigm for DL algorithms to preserve
data privacy. Although FL helps reduce privacy leakage by avoiding transferring client data, it …

Federated learning (FL) brings collaborative intelligence into industries without centralized
training data to accelerate the process of Industry 4.0 on the edge computing level. FL solves …