4 papers
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…
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…
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…