2 papers
cs.LG2026
Semantic Communication-Enhanced Split Federated Learning for Vehicular Networks: Architecture, Challenges, and Case Study
Lu Yu, Zheng Chang, Ying-Chang Liang
Vehicular edge intelligence (VEI) is vital for future intelligent transportation systems. However, traditional centralized learning in dynamic vehicular networks faces significant…
cs.LG2024
Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks
Lu Yu, Zheng Chang, Yunjian Jia +1
The integration of autonomous driving technologies with vehicular networks presents significant challenges in privacy preservation, communication efficiency, and resource allocatio…