… federated learning, this paper proposes a blockchain-based decentralized federated learning
method for edge computing … between local devices and edge servers and an optimized …

… In this paper, we have presented a cybertwin assisted AFL mechanism for realizing efficient
edge computing. For flexible and effective edge computing resource utilization, we have …

… -edge environment is defined in Section 3. Thereafter, a privacy-aware distributed learning
scheme with federated learning … on DDPG with federated learning is proposed in this article. …

… Federated learning (FL), as one of novel machine learning frameworks, has been widely
applied in edge … framework in edge computing environment, and especially the edge resources …

… asynchronous FL particularly in edge computing domains, even … of AFL-DAG for edge
computing applications. To provide a … by investigating a popular edge computing application, the …

… a lot of computing resources and data … federated learning application trading platform
called FLEX, on which users can buy and sell computing resources for training machine learning …

… Performance of federated learning in a multi-access edge computing (MEC) network suffers
from slow convergence due to heterogeneity and stochastic fluctuations in compute power …

… Federated Learning (PFL) is a new Federated Learning (FL) … user equipments (UEs) in
mobile edge computing (MEC) networks. … to the edge server (ES) synchronously for edge model …

… To address these issues, we propose a novel federated learning communication framework
FedComp that achieves a significant compression ratio while maintaining comparable …

… machine learning method known as federated learning (FL) … , facilitating collaborative machine
learning training of complex … in federated learning, machine learning, and edge computing…