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 …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Federated learning for generalization, robustness, fairness: A survey and benchmark
Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of federated learning, an …
collaboration among different parties. Recently, with the popularity of federated learning, an …
A survey of incentive mechanism design for federated learning
Federated learning is promising in enabling large-scale machine learning by massive
clients without exposing their raw data. It can not only enable the clients to preserve the …
clients without exposing their raw data. It can not only enable the clients to preserve the …
Non-orthogonal multiple access assisted federated learning via wireless power transfer: A cost-efficient approach
Federated learning (FL) has been considered as a promising paradigm for enabling
distributed training/learning in many machine-learning services without revealing users' …
distributed training/learning in many machine-learning services without revealing users' …
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 …
A comprehensive review on artificial intelligence/machine learning algorithms for empowering the future IoT toward 6G era
The evolution of the wireless network systems over decades has been providing new
services to the users with the help of innovative network and device technologies. In recent …
services to the users with the help of innovative network and device technologies. In recent …
Survey on digital twin edge networks (DITEN) toward 6G
The next generation (6G) wireless systems aim to cater to the Internet of Everything (IoE)
and revolutionize customer services and applications to a fully intelligent and autonomous …
and revolutionize customer services and applications to a fully intelligent and autonomous …
Towards fairness-aware federated learning
Recent advances in federated learning (FL) have brought large-scale collaborative machine
learning opportunities for massively distributed clients with performance and data privacy …
learning opportunities for massively distributed clients with performance and data privacy …
Federated learning with fair incentives and robust aggregation for UAV-aided crowdsensing
Unmanned aerial vehicles (UAVs) combined with artificial intelligence (AI) have recently
gathered significant interest to enable intelligent and on-demand crowdsensing …
gathered significant interest to enable intelligent and on-demand crowdsensing …