Incentivizing Differentially Private Federated Learning: A Multidimensional Contract Approach
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3050163
Abstract: Federated learning is a promising tool in the Internet-of-Things (IoT) domain for training a machine learning model in a decentralized manner. Specifically, the data owners (e.g., IoT device consumers) keep their raw data and only… read more here.
Keywords: private federated; federated learning; model; incentive mechanism ... See more keywords
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3168066
Abstract: Federated learning (FL), as a disruptive machine learning (ML) paradigm, enables the collaborative training of a global model over decentralized local data sets without sharing them. It spans a wide scope of applications from the… read more here.
Keywords: intelligent surface; federated learning; differentially private; private federated ... See more keywords
Boosting Accuracy of Differentially Private Federated Learning in Industrial IoT With Sparse Responses
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3161517
Abstract: Empowered by 5G, it has been extensively explored by existing works on the deployment of differentially private federated learning (DPFL) in the Industrial Internet of Things (IIoT). Through federated learning, decentralized IIoT devices can collaboratively… read more here.
Keywords: accuracy; federated learning; differentially private; private federated ... See more keywords