Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch

Author:

Lebeda Christian Janos1ORCID,Tetek Jakub2ORCID

Affiliation:

1. Basic Algorithms Research Copenhagen & IT University of Copenhagen, Copenhagen, Denmark

2. Basic Algorithms Research Copenhagen & University of Copenhagen, Copenhagen, Denmark

Funder

Villum Fonden

Publisher

ACM

Reference32 articles.

1. Mergeable summaries

2. Apple. [n.,d.]. Differential Privacy Overview - Apple. https://www.apple.com/privacy/docs/Differential_Privacy_Overview.pdf Retrieved April 13, 2023 from Apple. [n.,d.]. Differential Privacy Overview - Apple. https://www.apple.com/privacy/docs/Differential_Privacy_Overview.pdf Retrieved April 13, 2023 from

3. Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access

4. Differential Privacy on Finite Computers

5. Raef Bassily , Kobbi Nissim , Uri Stemmer , and Abhradeep Guha Thakurta . 2017 . Practical locally private heavy hitters . Advances in Neural Information Processing Systems , Vol. 30 (2017). Raef Bassily, Kobbi Nissim, Uri Stemmer, and Abhradeep Guha Thakurta. 2017. Practical locally private heavy hitters. Advances in Neural Information Processing Systems , Vol. 30 (2017).

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2. Differential Private Histogram Publication with Background Knowledge;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

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