US EditionNew Defense Strategy for Federated Learning, Capping Accuracy Loss at 0.47%
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New Defense Strategy for Federated Learning, Capping Accuracy Loss at 0.47%
Beihang University researchers unveil a new federated learning poisoning-attack mitigation strategy to cap accuracy losses under 1% on MNIST and under 4% on CIFAR-10, bolstering AI security and privacy in healthcare, autonomous vehicles, and finance.
·Charlottesville, United States
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