The Cost of Adaptation under Differential Privacy

Music City Center 

In this talk, I will discuss adaptation in the context of estimating a functional of an unknown density under differential privacy constraints. The talk is based on joint work with Tony Cai and Abhinav Chakraborty, in which we study derive theoretical performance upper- and lower-bounds for methods that adapt between different classes, and exhibit differentially private methods that successfully adapt between unknown function classes. Our theory shows that for certain classes of functions, the cost of adaptation can be substantially higher for adaptive differentially private protocols than their non-private counterparts.