Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent

Shuang Song, Thomas Steinke, Om Thakkar +1

We revisit the well-studied problem of differentially private empirical risk minimization (ERM). We show that for unconstrained convex generalized linear models (GLMs), one can obt…