"How to Make Your Approximation Algorithm Private: A Black-Box ..."

Jeremiah Blocki et al. (2022)

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DOI: 10.48550/ARXIV.2210.03831

access: open

type: Informal or Other Publication

metadata version: 2024-02-05

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  - https://dblp.org/rec/journals/corr/abs-2210-03831
Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou:
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. CoRR abs/2210.03831 (2022)

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