3 papers
cs.NI2026
Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
Hanzhi Yu, Hasan Farooq, Julien Forgeat +4
In this paper, we investigate a novel digital network twin (DNT) assisted deep learning (DL) model training framework. In particular, we consider a physical network where a base st…
cs.LG2025
Through the telecom lens: Are all training samples important?
Shruti Bothe, Illyyne Saffar, Aurelie Boisbunon +3
The rise of AI in telecommunications, from optimizing Radio Access Networks to managing user experience, has sharply increased data volumes and training demands. Telecom data is of…
cs.LG2025
Computation- and Communication-Efficient Online FL for Resource-Constrained Aerial Vehicles
Ferdous Pervej, Richeng Jin, Md Moin Uddin Chowdhury +3
Privacy-preserving distributed machine learning (ML) and aerial connected vehicle (ACV)-assisted edge computing have drawn significant attention lately. Since the onboard sensors o…