Improved Differentially Private Regression via Gradient Boosting

Shuai Tang, Sergul Aydore, Michael Kearns +5

We revisit the problem of differentially private squared error linear regression. We observe that existing state-of-the-art methods are sensitive to the choice of hyperparameters -…