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Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures., , , , and . Proc. VLDB Endow., 16 (13): 4160-4173 (2023)Practical Differential Privacy via Grouping and Smoothing., and . Proc. VLDB Endow., 6 (5): 301-312 (2013)Differentially Private Event Sequences over Infinite Streams., , , and . Proc. VLDB Endow., 7 (12): 1155-1166 (2014)Differentially Private Histograms for Range-Sum Queries: A Modular Approach., , and . CoRR, (2015)Shortest Path Computation on Air Indexes., and . Proc. VLDB Endow., 3 (1): 747-757 (2010)Map-matched trajectory compression., , and . J. Syst. Softw., 86 (6): 1566-1579 (2013)Engineering Methods for Differentially Private Histograms: Efficiency Beyond Utility., , and . IEEE Trans. Knowl. Data Eng., 31 (2): 315-328 (2019)εpsolute: Efficiently Querying Databases While Providing Differential Privacy., , , , and . CCS, page 2262-2276. ACM, (2021)Revealing the Unseen: How to Expose Cloud Usage While Protecting User Privacy., , and . ICDM Workshops, page 1011-1016. IEEE Computer Society, (2017)Trajectory Compression under Network Constraints., , and . SSTD, volume 5644 of Lecture Notes in Computer Science, page 392-398. Springer, (2009)