Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach

19 Mar 2020 Yi Liu James J. Q. Yu Jiawen Kang Dusit Niyato Shuyu Zhang

Existing traffic flow forecasting approaches by deep learning models achieve excellent success based on a large volume of datasets gathered by governments and organizations. However, these datasets may contain lots of user's private data, which is challenging the current prediction approaches as user privacy is calling for the public concern in recent years... (read more)

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