Free gap information from the differentially private sparse vector and noisy max mechanisms
Free gap information from the differentially private sparse vector and noisy max mechanisms
Noisy Max and Sparse Vector are selection algorithms for differential privacy and serve as building blocks for more complex algorithms. In this paper we show that both algorithms can release additional information for free (i.e., at no additional privacy cost). Noisy Max is used to return the approximate maximizer among …