IEEE

Tackling Class Imbalance and Client Heterogeneity for Split Federated Learning in Wireless Networks

Abstract: As the complexity of deep neural networks escalates, traditional federated learning (FL) frameworks increasingly struggle since the training overhead of the full model is costly for resource ...
IEEE

Mobility-Aware Federated Learning: Optimizing Performance with Interpretable Models and Wireless Channel Resource Allocation

Abstract: The integration of the Internet of Things (IoT) with Federated Learning (FL) offers a transformative approach to addressing the challenges of massive data processing and privacy preservation ...