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Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming

Summary: Studies frequency estimation across k parties under multiparty differential privacy (MDP), covering both one-shot aggregation and continual streaming. Achieves near-optimal privacy–communication tradeoffs, including an LDP error of √k/(e^ε−1) with near-linear communication. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12890
Venue
VLDB
Year
2022
Pagerank
5.6072422e-05
Overall Rank
7,488 | 48.63%
DOI
10.14778/3547305.3547312

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{huang_vldb22,
        title = {{Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming}},
        author = {Huang, Ziyue and Qiu, Yuan and Yi, Ke and Cormode, Graham},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {10},
        pages = {2058--2070},
        doi = {10.14778/3547305.3547312},
        url = {https://doi.org/10.14778/3547305.3547312},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
6,094 The Fast and the Private: Task-based Dataset Search 2024 CIDR 5.9786215e-05
6,421 Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System 2023 VLDB 5.8819368e-05
10,289 Sketch-based Secure Query Processing for Streaming Data 2026 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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