Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach

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 exploiti...

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Bibliographic Details
Main Authors: Dongdong Ye, Rong Yu, Miao Pan, Zhu Han
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Federated learning
vehicular edge computing
model aggregation
contract theory
Online Access:https://ieeexplore.ieee.org/document/8964354/

Internet

https://ieeexplore.ieee.org/document/8964354/

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