opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
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@inproceedings{Smith11,
    author = {Smith, Adam},
    title = {Privacy-Preserving Statistical Estimation with Optimal Convergence Rates},
    year = {2011},
    isbn = {9781450306911},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/1993636.1993743},
    doi = {10.1145/1993636.1993743},
    booktitle = {Proceedings of the Forty-Third Annual ACM Symposium on Theory of Computing},
    pages = {813–822},
    numpages = {10},
    keywords = {asymptotic distribution, statistical inference, differential privacy},
    location = {San Jose, California, USA},
    series = {STOC '11}
}