Boosting the accuracy of differentially private histograms through consistency
Boosting the accuracy of differentially private histograms through consistency
We show that it is possible to significantly improve the accuracy of a general class of histogram queries while satisfying differential privacy. Our approach carefully chooses a set of queries to evaluate, and then exploits consistency constraints that should hold over the noisy output. In a post-processing phase, we compute …