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Concurrent Composition for Differentially Private Continual Mechanisms

Summary: First general concurrent composition for continual DP under adaptive, interleaved queries and dataset updates, supporting event- and user-level neighboring. Characterizes when parallel composition survives updates—and its failure for approximate DP—with modular extensions to Rényi/f-DP and interactive LDP. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
2025
Venue
PODS
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,150 | 30.37%
DOI
10.1145/3801895

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BibTeX Citation

@inproceedings{henzinger_pods26,
        address = {New York, NY, USA},
        series = {{PODS} '26},
        title = {{Concurrent Composition for Differentially Private Continual Mechanisms}},
        url = {https://dl.acm.org/doi/10.1145/3801895},
        doi = {10.1145/3801895},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Henzinger, Monika and Safavi, Roodabeh and Vadhan, Salil},
        year = {2026}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,012 Understanding the Sparse Vector Technique for Differential Privacy 2017 VLDB 9.3073552e-05
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