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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)

Paper ID
1892
Venue
PODS
Year
2023
Pagerank
6.5160376e-05
Overall Rank
4,905 | 65.92%
DOI
10.1145/3584372.3588673

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
8,610 Differentially Private Hierarchical Heavy Hitters 2024 PODS 5.4598872e-05
10,366 Private Synthetic Data Generation in Bounded Memory 2025 PODS 5.1725247e-05
10,480 Approximate DBSCAN under Differential Privacy 2025 SIGMOD 5.1725247e-05
10,905 Streaming Algorithms with Few State Changes 2024 PODS 5.1725247e-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
447 Mergeable Summaries 2012 PODS 0.00018364636
3,022 Pan-private Algorithms Via Statistics on Sketches 2011 PODS 7.9055062e-05
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