On the feasibility of federated learning towards on-demand client deployment at the edge
Nowadays, researchers are investing their time and devoting their efforts in developing and
motivating the 6G vision and resources that are not available in 5G. Edge computing and …
motivating the 6G vision and resources that are not available in 5G. Edge computing and …
Multi-agent federated reinforcement learning for resource allocation in uav-enabled internet of medical things networks
In the 5G/B5G network paradigms, intelligent medical devices known as the Internet of
Medical Things (IoMT) have been used in the healthcare industry to monitor remote users' …
Medical Things (IoMT) have been used in the healthcare industry to monitor remote users' …
A systematic literature review on client selection in federated learning
C Smestad, J Li - Proceedings of the 27th International Conference on …, 2023 - dl.acm.org
With the arising concerns of privacy within machine learning, federated learning (FL) was
invented in 2017, in which the clients, such as mobile devices, train a model and send the …
invented in 2017, in which the clients, such as mobile devices, train a model and send the …
Adaptive upgrade of client resources for improving the quality of federated learning model
S AbdulRahman, H Ould-Slimane… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Conventional systems are usually constrained to store data in a centralized location. This
restriction has either precluded sensitive data from being shared or put its privacy on the …
restriction has either precluded sensitive data from being shared or put its privacy on the …
Semi-supervised federated learning over heterogeneous wireless iot edge networks: Framework and algorithms
Federated learning (FL) is a promising paradigm for future sixth-generation wireless systems
to underpin network edge intelligence for smart cities applications. However, most of the …
to underpin network edge intelligence for smart cities applications. However, most of the …
Fair selection of edge nodes to participate in clustered federated multitask learning
Clustered federated Multitask learning is introduced as an efficient technique when data is
unbalanced and distributed amongst clients in a non-independent and identically distributed …
unbalanced and distributed amongst clients in a non-independent and identically distributed …
Edgeml: towards network-accelerated federated learning over wireless edge
Federated learning (FL) is a distributed machine learning technology for next-generation AI
systems that allows a number of workers, ie, edge devices, collaboratively learn a shared …
systems that allows a number of workers, ie, edge devices, collaboratively learn a shared …
Delay-constrained client selection for heterogeneous federated learning in intelligent transportation systems
Federated learning has been claimed as a solution in intelligent transportation systems,
which allows for the implementation of distributed machine learning while ensuring privacy …
which allows for the implementation of distributed machine learning while ensuring privacy …
Training Machine Learning models at the Edge: A Survey
Edge Computing (EC) has gained significant traction in recent years, promising enhanced
efficiency by integrating Artificial Intelligence (AI) capabilities at the edge. While the focus …
efficiency by integrating Artificial Intelligence (AI) capabilities at the edge. While the focus …
Adaptive asynchronous federated learning
Federated Learning enables data owners to train an artificial intelligence model
collaboratively while keeping all the training data locally, reducing the possibility of personal …
collaboratively while keeping all the training data locally, reducing the possibility of personal …