The Median Mechanism: Interactive and Efficient Privacy with Multiple Queries

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How researchers see this paper

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Boosting and Differential Privacy (2010, background): “(Previously, Roth and Roughgarden [22] gave such an interactive mechanism that achieved similar accuracy and efficiency to [3].)”
A Simple and Practical Algorithm for Differentially Private Data Release (2010, background): “Since [2], subsequent work [6, 12, 23, 16] has focused on computationally more eﬃcient algorithms (i.e., polynomial in | D | ) as well as algorithms that work in the interactive query setting.”
Optimizing linear counting queries under differential privacy (2009, background): “Roth and Roughgarden [15] consider the interactive setting, in which queries arrive over time and must be answered immediately without knowledge of future queries.”
Distance makes the types grow stronger: a calculus for differential privacy (2010, methodology): “More gene ral mechanisms for directly noising types other than R also exist, such as the exponential mechanism [24], and techniques have been developed to reduce the amount of noise required for repeate d queries, such as the median mechanism [31].”
Differential privacy for collaborative security (2010, background): “Notably, Roth and Roughgarden’s recent work on the median mechanism [ 29 ] offers an exponential increase in the (still finite) number of queries that can be asked over the same data.”