2 papers
cs.LG2026
Energy-Efficient Hierarchical Federated Anomaly Detection for the Internet of Underwater Things via Selective Cooperative Aggregation
Kenechi Omeke, Michael Mollel, Lei Zhang +2
Anomaly detection is a core service in the Internet of Underwater Things, yet training accurate distributed models underwater is difficult because acoustic links are low-bandwidth,…
eess.SP2024
Deep Reinforcement Learning for Energy-Efficient on the Heterogeneous Computing Architecture
Zheqi Yu, Chao Zhang, Pedro Machado +4
The growing demand for optimal and low-power energy consumption paradigms for IOT devices has garnered significant attention due to their cost-effectiveness, simplicity, and intell…