4 papers
Energy Efficient Federated Learning with Hyperdimensional Computing over Wireless Communication Networks
Yahao Ding, Yinchao Yang, Jiaxiang Wang +3
In this paper, we investigate a problem of minimizing total energy consumption for secure federated learning (FL) over wireless edge networks. To address the high computational cos…
Energy Efficient Federated Learning with Hyperdimensional Computing (HDC)
Yahao Ding, Yinchao Yang, Jiaxiang Wang +4
This paper investigates the problem of minimizing total energy consumption for secure federated learning (FL) in wireless edge networks, a key paradigm for decentralized big data a…
A Secure and Private Distributed Bayesian Federated Learning Design
Nuocheng Yang, Sihua Wang, Zhaohui Yang +3
Distributed Federated Learning (DFL) enables decentralized model training across large-scale systems without a central parameter server. However, DFL faces three critical challenge…
Federated Split Learning for Resource-Constrained Robots in Industrial IoT: Framework Comparison, Optimization Strategies, and Future Directions
Wanli Ni, Hui Tian, Shuai Wang +3
Federated split learning (FedSL) has emerged as a promising paradigm for enabling collaborative intelligence in industrial Internet of Things (IoT) systems, particularly in smart f…