Lower Bounds for Public-Private Learning under Distribution Shift

Amrith Setlur, Pratiksha Thaker, Jonathan Ullman

The most effective differentially private machine learning algorithms in practice rely on an additional source of purportedly public data. This paradigm is most interesting when th…