Topic: distributed-training
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Federated averaging: local training, client weighting and heterogeneous data
Federated averaging combines model updates computed on separate clients. Its behavior depends on local training, aggregation weights and client differences; keeping raw data local does not itself provide a formal privacy guarantee.
Machine-readable: JSON