Locating a small cluster privately
Publication information:
Nissim, Kobbi, Uri Stemmer, and Salil Vadhan. “Locating a Small Cluster Privately”. In Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS ‘16), 413-27. ACM, 2016.
Abstract
Version History: Full version posted as arXiv:1604.05590 [cs.DS].
We present a new algorithm for locating a small cluster of points with differential privacy [Dwork, McSherry, Nissim, and Smith, 2006]. Our algorithm has implications to private data exploration, clustering, and removal of outliers. Furthermore, we use it to significantly relax the requirements of the sample and aggregate technique [Nissim, Raskhodnikova, and Smith, 2007], which allows compiling of “off the shelf” (non-private) analyses into analyses that preserve differential privacy.