Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …
solutions to replace the traditional model-driven approaches that proved to be not rich …
Federated learning in mobile edge networks: A comprehensive survey
In recent years, mobile devices are equipped with increasingly advanced sensing and
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
[HTML][HTML] Federated learning for healthcare informatics
With the rapid development of computer software and hardware technologies, more and
more healthcare data are becoming readily available from clinical institutions, patients …
more healthcare data are becoming readily available from clinical institutions, patients …
Incentive mechanism for reliable federated learning: A joint optimization approach to combining reputation and contract theory
Federated learning is an emerging machine learning technique that enables distributed
model training using local datasets from large-scale nodes, eg, mobile devices, but shares …
model training using local datasets from large-scale nodes, eg, mobile devices, but shares …
Reliable federated learning for mobile networks
Federated learning, as a promising machine learning approach, has emerged to leverage a
distributed personalized dataset from a number of nodes, for example, mobile devices, to …
distributed personalized dataset from a number of nodes, for example, mobile devices, to …
Federated learning for vehicular internet of things: Recent advances and open issues
Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …
purpose of collaborative learning from a large amount of data that belong to different parties …
Blockchain and federated learning for collaborative intrusion detection in vehicular edge computing
H Liu, S Zhang, P Zhang, X Zhou… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The vehicular networks constructed by interconnected vehicles and transportation
infrastructure are vulnerable to cyber-intrusions due to the expanded use of software and the …
infrastructure are vulnerable to cyber-intrusions due to the expanded use of software and the …
Fusion of federated learning and industrial Internet of Things: A survey
Abstract Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry
4.0 and paves an insight for new industrial era. Nowadays smart machines and smart …
4.0 and paves an insight for new industrial era. Nowadays smart machines and smart …
Deep reinforcement learning assisted federated learning algorithm for data management of IIoT
The continuous expanded scale of the industrial Internet of Things (IIoT) leads to IIoT
equipments generating massive amounts of user data every moment. According to the …
equipments generating massive amounts of user data every moment. According to the …