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iReduct: differential privacy with reduced relative errors.

, , , and . SIGMOD Conference, page 229-240. ACM, (2011)

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Avoiding Bias when Aggregating Relational Data with Degree Disparity, , and . Proceedings of the Twentieth International Conference on Machine Learning (ICML), page 274--281. (2003)EKTELO: A Framework for Defining Differentially-Private Computations., , , , , and . SIGMOD Conference, page 115-130. ACM, (2018)Optimizing Histogram Queries under Differential Privacy, , , , and . CoRR, (2009)Differential Privacy in the Wild: A Tutorial on Current Practices & Open Challenges., , and . SIGMOD Conference, page 1727-1730. ACM, (2017)How PhD students at research universities can prepare for a career at a liberal arts college (abstract only)., , and . SIGCSE, page 752. ACM, (2013)Relationship privacy: output perturbation for queries with joins., , , and . PODS, page 107-116. ACM, (2009)Accurate Estimation of the Degree Distribution of Private Networks., , , and . ICDM, page 169-178. IEEE Computer Society, (2009)IoT-Detective: Analyzing IoT Data Under Differential Privacy., , , , , , and . SIGMOD Conference, page 1725-1728. ACM, (2018)Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy., , , , , , , , , and 3 other author(s). CoRR, (2022)A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy., , , and . CoRR, (2014)