DBScholar

Back to papers

Improved Lower Bounds for Privacy under Continual Release

Summary: Proves polynomial continual-release lower bounds for insertion-only graph statistics and simultaneous norm estimation, overturning the presumed insertion/deletion gap. Multiplicative slack restores polylogarithmic error, while new item-level product lower bounds follow via 1-Way-Marginals reductions. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
2033
Venue
PODS
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,158 | 30.31%
DOI
10.1145/3801903

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{aryanfard_pods26,
        address = {New York, NY, USA},
        series = {{PODS} '26},
        title = {{Improved Lower Bounds for Privacy under Continual Release}},
        url = {https://dl.acm.org/doi/10.1145/3801903},
        doi = {10.1145/3801903},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Aryanfard, Bardiya and Henzinger, Monika and Saulpic, David and Sricharan, A. R.},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers