Incentive mechanisms for federated learning: From economic and game theoretic perspective

X Tu, K Zhu, NC Luong, D Niyato… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
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 …

A comprehensive survey of incentive mechanism for federated learning

R Zeng, C Zeng, X Wang, B Li, X Chu - ar** our lives and works. Billions of AIoT devices around the world are …

[HTML][HTML] Federated Reinforcement Learning for Collaborative Intelligence in UAV-assisted C-V2X Communications

A Gupta, X Fernando - Drones, 2024 - mdpi.com
This paper applies federated reinforcement learning (FRL) in cellular vehicle-to-everything
(C-V2X) communication to enable vehicles to learn communication parameters in …

Incentive mechanism for differentially private federated learning in industrial Internet of Things

Y Xu, M **ao, H Tan, A Liu, G Gao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a newly emerging distributed machine learning paradigm,
whereby a server can coordinate multiple clients to jointly train a learning model by using …

Auction-promoted trading for multiple federated learning services in UAV-aided networks

Z Cheng, M Liwang, X **a, M Min… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) represents a promising distributed machine learning paradigm that
allows smart devices to collaboratively train a shared model via providing local data sets …

Fedtor: An anonymous framework of federated learning in internet of things

Y Chen, Y Su, M Zhang, H Chai… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
With a large number of devices and a wealth of user data sets, the Internet of Things (IoT)
has become a great host for federated learning (FL). At the same time, the massive amount …