A federated learning method that compresses gradients and weights model aggregation by gradient correlation attains state-of-the-art traffic prediction at roughly one-fortieth of the communication cost.
Joint ran slicing and computation offloading for autonomous vehicular networks: A learning-assisted hierarchical approach,
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Gradient Compression and Correlation Driven Federated Learning for Wireless Traffic Prediction
A federated learning method that compresses gradients and weights model aggregation by gradient correlation attains state-of-the-art traffic prediction at roughly one-fortieth of the communication cost.