Xiao-Na Jiang

Delay-Driven Vehicle Scheduling and Resource Optimization for Multi-Task Federated Learning in Heterogeneous Vehicular Networks

Federated learning (FL) has become a promising paradigm for privacy-preserving and communication-efficient model training in vehicular networks. With the continuous expansion of vehicular networks, multiple FL tasks are often initiated concurrently by moving vehicles, which poses substantial challenges to the conventio...