AdaFed: Adaptive Selective Aggregation for Heterogeneous Federated Learning in Autonomous Driving
We present a comprehensive empirical study of federated learning (FL) for seven heterogeneous autonomous driving models and propose AdaFed, an adaptive selective aggregation strategy. We introduce a tier-based partial backbone sharing framework that groups models by shared architectural components (ResNet-34/50 backbon...