Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach
Federated learning is a newly emerged distributed machine learning paradigm, where the clients are allowed to individually train local deep neural network (DNN) models with local data and then jointly aggregate a global DNN model at the central server.Vehicular edge computing (VEC) aims at exploiting the lintusakset computation and communication re