Optimal Density Estimation under Central Privacy Constraints

The core message of this article is that the cost of central privacy in density estimation depends on the smoothness of the underlying density and the privacy budget. For Lipschitz densities, the minimax rate of estimation is degraded when the privacy budget is small, but for smoother Sobolev densities, the minimax rate can be preserved in certain privacy regimes.