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dc:creator <https://dblp.l3s.de/d2r/resource/authors/Samson_Zhou>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Tamalika_Mukherjee>
foaf:homepage <http://dx.doi.org/doi.org%2F10.4230%2FLIPIcs.APPROX%2FRANDOM.2023.59>
foaf:homepage <https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2023.59>
dc:identifier DBLP conf/approx/BlockiGMZ23 (xsd:string)
dc:identifier DOI doi.org%2F10.4230%2FLIPIcs.APPROX%2FRANDOM.2023.59 (xsd:string)
dcterms:issued 2023 (xsd:gYear)
rdfs:label How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. (xsd:string)
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swrc:pages 59:1-59:24 (xsd:string)
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dc:title How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. (xsd:string)
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rdf:type swrc:InProceedings
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