… computing power, and data security threats. Therefore, we propose a ubiquitous intelligent
federated learning … provides privacy protection for data under edge computing. First, we train …

… federated learning through adaptive model pruning. Specifically, we adopt a structured model
pruning approach for federated learning … We then propose an MAB based online learning …

… technique issues, the optimization design of federated learning in the MEC systems is studied
… cost of federated learning, we provide a framework of deploying federated learning in the …

… The rest of the paper is organized as follows: In Section 2, we discuss the related works on
federated learning, edge computing, and privacy preservation followed by a background of …

… With the advent of 5G, edge computing and federated learning have attracted … a federated
learning system that is more suitable for collaborative learning of discrete nodes in edge …

… Also, federated learning is very close to the distributed learning paradigm. In previous studies,
DRL or DL has been used in each device… We solve this issue by using federated learning. …

… This paper presents the FedSens, a federated learning framework to perform privacy-aware …
mobile edge computing systems. We develop a novel curiosity driven reinforcement learning …

… a set of federated learning (FL) protocols for future Internet architectures, which integrate
the edge computing with the Internet of Things (IoT) known as ”IoT edge computing”. The …

… The main challenges of applying federated learning to MEC … on the resource-constraint
mobile edge devices; (2) existing … private federated learning scheme in mobile edge computing, …

… the computation ability of each edge device to train local models and … -based Privacy-Preserving
Federated Learning (PPFL) … Federated Learning scheme (VPFL) for edge computing …