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Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
Hierarchical federated learning with social context clustering-based participant selection for internet of medical things applications
The proliferation in embedded and communication technologies made the concept of the
Internet of Medical Things (IoMT) a reality. Individuals' physical and physiological status can …
Internet of Medical Things (IoMT) a reality. Individuals' physical and physiological status can …
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 …
Efficient parallel split learning over resource-constrained wireless edge networks
The increasingly deeper neural networks hinder the democratization of privacy-enhancing
distributed learning, such as federated learning (FL), to resource-constrained devices. To …
distributed learning, such as federated learning (FL), to resource-constrained devices. To …
Secure and efficient federated learning for smart grid with edge-cloud collaboration
With the prevalence of smart appliances, smart meters, and Internet of Things (IoT) devices
in smart grids, artificial intelligence (AI) built on the rich IoT big data enables various energy …
in smart grids, artificial intelligence (AI) built on the rich IoT big data enables various energy …
Incentive mechanisms for federated learning: From economic and game theoretic perspective
Federated learning (FL) becomes popular and has shown great potentials in training large-
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …
Communication-efficient distributed learning: An overview
Distributed learning is envisioned as the bedrock of next-generation intelligent networks,
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
Optimizing federated learning with deep reinforcement learning for digital twin empowered industrial IoT
The accelerated development of the Industrial Internet of Things (IIoT) is catalyzing the
digitalization of industrial production to achieve Industry 4.0. In this article, we propose a …
digitalization of industrial production to achieve Industry 4.0. In this article, we propose a …
An incentive mechanism of incorporating supervision game for federated learning in autonomous driving
Federated learning (FL), as a distributed machine learning technology, allows large-scale
nodes to utilize local datasets for model training and sharing without revealing privacy …
nodes to utilize local datasets for model training and sharing without revealing privacy …