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March Boedihardjo1, Thomas Strohmer2, Roman Vershynin3

  • 1Department of Mathematics, Michigan State University, East Lansing, USA.

Probability theory and related fields
|May 28, 2024
PubMed
概括

这项研究引入了度量隐私,这是差异隐私的强有力的概括,以创建准确的私人合成数据用于各种分析. 它克服了现有方法的局限性,增强了机器学习任务的隐私保护数据共享.

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