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Balls-and-Bins Sampling for DP-SGD
We introduce the Balls-and-Bins sampling for differentially private (DP) optimization methods such as DP-SGD.
Optimal Unbiased Randomizers for Regression with Label Differential Privacy
We propose a new family of label randomizers for training regression models under the constraint of label differential privacy (DP).
Regression with Label Differential Privacy
We study the task of training regression models with the guarantee of label differential privacy (DP).
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