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Kamino: Constraint-Aware Differentially Private Data Synthesis

Summary: Kamino synthesizes databases with differential privacy while explicitly preserving schema/integrity constraints and tuple–attribute dependencies. Unlike application-specific synthesizers, it maintains structural validity and correlations, improving downstream classification and marginal-query utility. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12559
Venue
VLDB
Year
2021
Pagerank
7.4344343e-05
Overall Rank
3,412 | 76.60%
DOI
10.14778/3467861.3467876

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BibTeX Citation

@article{ge_vldb21,
        title = {{Kamino: Constraint-Aware Differentially Private Data Synthesis}},
        author = {Ge, Chang and Mohapatra, Shubhankar and He, Xi and Ilyas, Ihab F.},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {10},
        pages = {1886--1899},
        doi = {10.14778/3467861.3467876},
        url = {https://doi.org/10.14778/3467861.3467876},
        year = {2021}
}

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