4 papers · 1 filter
Resilient Decentralized Wireless Federated Learning via Gradient Tracking with AdamW
Nguyen Van Thieu, Ti Ti Nguyen, Ons Aouedi +2
Wireless Internet-of-Things (IoT) edge networks require decentralized learning (DecL) methods that can operate reliably under both heterogeneous local data and communication-constr…
FedQoS: Federated QoS-Risk Learning for Heterogeneous Indoor-Outdoor Access Selection
Nguyen Van Thieu, Ti Ti Nguyen, Ons Aouedi +3
Reliable access selection in dynamic and heterogeneous indoor-outdoor environments is challenging because instantaneous radio measurements alone cannot capture future QoS degradati…
GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems
Zheng Lin, Ons Aouedi, Zihan Fang +4
The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge devices. Parallel split learning (P…
FLEXIBLE: Forecasting Cellular Traffic by Leveraging Explicit Inductive Graph-Based Learning
Duc Thinh Ngo, Kandaraj Piamrat, Ons Aouedi +2
From a telecommunication standpoint, the surge in users and services challenges next-generation networks with escalating traffic demands and limited resources. Accurate traffic pre…