NA Jalali, H Chen - Tsinghua Science and Technology, 2023 - ieeexplore.ieee.org
The widespread use of the Internet of Things (IoTs) and the rapid development of artificial intelligence technologies have enabled applications to cross commercial and industrial …
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis on enabling software and hardware platforms, protocols, real-life applications and use …
L Ge, H Li, X Wang, Z Wang - Neurocomputing, 2023 - Elsevier
Advances in the new generation of Internet of Things (IoT) technology are propelling the growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon decentralized data and training that brings learning to the edge or directly on-device. FL is a …
Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …
In the past decades, artificial intelligence (AI) has achieved unprecedented success, where statistical models become the central entity in AI. However, the centralized training and …
S Rachakonda, S Moorthy, A Jain… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Federated Learning (FL) is a machine learning technique that enables to collaboratively learn valuable information across devices or sites without moving the data. In FL, the model …
C Briggs, Z Fan, P Andras - Federated Learning Systems: Towards Next …, 2021 - Springer
Abstract The Internet-of-Things (IoT) generates vast quantities of data. Much of this data is attributable to human activities and behavior. Collecting personal data and executing …
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 …