Heavy Hitters and the Structure of Local Privacy
Summary: Achieves heavy-hitters error optimal in users, domain, privacy, and failure probability under local DP, using a new structural lower bound. It also proves √k group-privacy degradation and a pure/approximate local-privacy equivalence for noninteractive protocols. (summarized by gpt-5.6-luna on Jul 26 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mark Bun (Princeton University)
- 2. Jelani Nelson (Harvard University)
- 3. Uri Stemmer (Weizmann Institute of Science)
BibTeX Citation
@inproceedings{bun_pods18,
address = {New York, NY, USA},
series = {{PODS} '18},
title = {{Heavy Hitters and the Structure of Local Privacy}},
url = {https://dl.acm.org/doi/10.1145/3196959.3196981},
doi = {10.1145/3196959.3196981},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Bun, Mark and Nelson, Jelani and Stemmer, Uri},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 2,862 | Privacy via Pseudorandom Sketches | 2006 | PODS | 8.0209471e-05 |
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