D Yang, W Zhang, Q Ye, C Zhang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we present a three-layer (ie, device, field, and factory layers) deterministic federated learning (FL) framework, named DetFed, which accelerates collaborative learning …
LT Yang, R Zhao, D Liu, W Lu… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The deep fusion of human-centered Cyber-Physical-Social Systems (CPSSs) has attracted widespread attention worldwide and big data as the blood of CPSSs could lay a solid data …
L Chen, L Fan, X Lei, TQ Duong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we study a relay-assisted federated edge learning (FEEL) network under latency and bandwidth constraints. In this network, users collaboratively train a global model …
MS Al-Abiad, MZ Hassan… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Distributed machine learning (ML) algorithms are imperative for the next-generation Internet of Things (IoT) networks, thanks to preserving the privacy of users' data and efficient usage …
L Zhang, Y Wu, L Chen, L Fan… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
In this article, we propose a novel federated learning (FL) framework for wireless Internet of Medical Things (IoMT) based healthcare systems, where multiple mobile clients and one …
Z Lin, H Liu, YJA Zhang - IEEE Transactions on Wireless …, 2022 - ieeexplore.ieee.org
Federated learning (FL) has recently emerged as a promising technology to enable artificial intelligence (AI) at the network edge, where distributed mobile devices collaboratively train a …
MS Al-Abiad, M Obeed, MJ Hossain… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has emerged as a distributed machine learning (ML) technique to train models without sharing users' private data. In this paper, we introduce a decentralized …
H Zhang, K Zeng, S Lin - IEEE Transactions on Signal …, 2023 - ieeexplore.ieee.org
Introducing adaptiveness to federated learning has recently ushered in a new way to optimize its convergence performance. However, adaptive learning strategies originally …
S Hu, X Yuan, W Ni, X Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated learning (FL) can suffer from communication bottlenecks when deployed in mobile networks, limiting participating clients and deterring FL convergence. In this context …