FedIDM filters abnormal updates in federated learning by creating condensed data through distribution matching and rejecting updates that deviate or cause high loss on that data.
Machine learning with adversaries: Byzantine toler- ant gradient descent.Advances in neural information processing systems, 30
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FedIDM: Achieving Fast and Stable Convergence in Byzantine Federated Learning through Iterative Distribution Matching
FedIDM filters abnormal updates in federated learning by creating condensed data through distribution matching and rejecting updates that deviate or cause high loss on that data.