Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch
Summary: (ε,δ)-DP mechanism for Misra‑Gries sketches on streams that adds noise independent of sketch size, achieving error matching best non‑streaming bounds up to constants. Also a simple post‑processing variant yields <2× non‑streaming noise for ε‑DP, improving prior linear‑in‑k noise. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,522 | Differentially Private Hierarchical Heavy Hitters | 2024 | PODS | 4.4937074e-05 |
| 10,354 | Private Synthetic Data Generation in Bounded Memory | 2025 | PODS | 4.1945683e-05 |
| 10,470 | Approximate DBSCAN under Differential Privacy | 2025 | SIGMOD | 4.1945683e-05 |
| 10,901 | Streaming Algorithms with Few State Changes | 2024 | PODS | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 402 | Mergeable Summaries | 2012 | PODS | 0.00024196343 |
| 2,894 | Pan-private Algorithms Via Statistics on Sketches | 2011 | PODS | 7.9474698e-05 |
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