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Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
- Machine learning models are vulnerable to attacks on privacy and model accuracy.
- Standard differentially private model training is inadequate for strong certified robustness guarantees.
- DP-CERT is a simple and effective method that combines differential privacy and robustness guarantees.
- DP-CERT reduces Lipschitz constants and improves certified accuracy on CIFAR10.
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