Private Synthetic Data Generation in Bounded Memory
Summary: PrivHP provides epsilon-DP synthetic data for streams via a bounded-memory private hierarchical decomposition approximating the input CDF. It uses a pruning parameter k and tail_k to trade space for utility, with private sketches achieving M = O(k log^2|X|) and Wasserstein bounds. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Rayne Holland (Commonwealth Scientific and Industrial Research Organisation (Data61))
- 2. Seyit Camtepe (Commonwealth Scientific and Industrial Research Organisation (Data61))
- 3. Chandra Thapa (Commonwealth Scientific and Industrial Research Organisation (Data61))
- 4. Minhui Xue (Commonwealth Scientific and Industrial Research Organisation (Data61))
BibTeX Citation
@inproceedings{holland_pods25,
address = {New York, NY, USA},
series = {{PODS} '25},
title = {{Private Synthetic Data Generation in Bounded Memory}},
url = {https://dl.acm.org/doi/10.1145/3725244},
doi = {10.1145/3725244},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Holland, Rayne and Camtepe, Seyit and Thapa, Chandra and Xue, Minhui},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 121 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.00031639377 |
| 130 | Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release | 2007 | PODS | 0.00030604781 |
| 567 | Understanding Hierarchical Methods for Differentially Private Histograms | 2013 | VLDB | 0.00016420715 |
| 777 | Tight Bounds for Lp Samplers, Finding Duplicates in Streams, and Related Problems | 2011 | PODS | 0.0001410593 |
| 1,308 | PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions | 2016 | SIGMOD | 0.00011216361 |
| 3,854 | Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch | 2023 | PODS | 7.0723123e-05 |
| 7,831 | Differentially Private Hierarchical Heavy Hitters | 2024 | PODS | 5.5357919e-05 |
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