REFOL detects concept drift per client with a KLD threshold and aggregates models via two-layer graph convolution, cutting communication and computation while keeping online traffic forecast errors close to the state of the art.
Privacy-preserving traffic flow prediction: A federated learning approach,
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REFOL: Resource-Efficient Federated Online Learning for Traffic Flow Forecasting
REFOL detects concept drift per client with a KLD threshold and aggregates models via two-layer graph convolution, cutting communication and computation while keeping online traffic forecast errors close to the state of the art.