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Hypothesis Testing Interpretations and Renyi Differential Privacy
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由 B Balle 著作2020被引用 119 次 — In this paper, we identify some conditions under which a privacy definition given in terms of a statistical divergence satisfies a similar interpretation.
Hypothesis Testing Interpretations and Renyi Differential ...
arXiv
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由 B Balle 著作2019被引用 119 次 — Abstract:Differential privacy is a de facto standard in data privacy, with applications in the public and private sectors.
Hypothesis Testing Interpretations and Rényi Differential Privacy
Proceedings of Machine Learning Research
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Proceedings of Machine Learning Research
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由 B Balle 著作2020被引用 119 次 — We use these two analytical tools to show that a privacy definition based on a divergence has a hypothesis test- ing interpretation in the sense described above ...
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Hypothesis Testing Interpretations and Rényi Differential ...
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由 B Balle 著作2019被引用 119 次 — We used these notions to study the hypothesis testing interpretation of relaxations of differential privacy based on the Rényi divergence.
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Hypothesis Testing Interpretations and Renyi Differential ...
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2024年10月6日 — Bibliographic details on Hypothesis Testing Interpretations and Renyi Differential Privacy.
Hypothesis Testing Interpretations and Renyi Differential ...
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2024年9月10日 — We show that the divergence used for differential privacy is 2-generated, and hence it satisfies the hypothesis testing interpretation. In ...
Hypothesis Testing Interpretations and Renyi Differential ...
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Differential privacy is a de facto standard in data privacy, with applicationsin the public and private sectors. One way of explaining differential privacy ...
佐藤 哲也 (Tetsuya Sato) - Hypothesis Testing ...
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Hypothesis Testing Interpretations and Renyi Differential Privacy ; 巻: 108 ; 号 ; 開始ページ: 2496 ; 終了ページ: 2506 ; 記述言語: 英語 ...
Borja Balle
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Hypothesis testing interpretations and renyi differential privacy. B Balle, G Barthe, M Gaboardi, J Hsu, T Sato. International Conference on Artificial ...
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Differential Privacy (DP) provides a formal privacy guarantee preventing adversaries with access to a machine learning model from extracting information about ...
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