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Federated learning can match centralized ML performance in bike-sharing demand forecasting, opening the door to privacy-preserving urban mobility solutions.
XGBoost crushes neural nets and statistical methods in EV charging demand forecasting, but federated learning provides a privacy-preserving path forward.
