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English(EN) Geometric Renyi Differential Privacy: Ricci Curvature Characterized by Heat Diffusion Mechanisms

新的隐私机制将几何分析、热扩散和差分隐私联系起来

研究人员引入了一种新的隐私机制,用于处理位于黎曼流形上的数据。这种新颖的方法在几何分析、热扩散模型和差分隐私之间建立了联系。该机制利用 Ricci 曲率提供 Renyi 差分隐私保证,对具有非负 Ricci 曲率的流形使用热扩散,对一般流形使用 Langevin 过程。 AI

影响 为流形值数据引入了新颖的隐私技术,可能影响隐私保护的机器学习应用。

排序理由 学术论文,介绍了一种用于流形值数据的新颖隐私机制。

在 arXiv stat.ML 阅读 →

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新的隐私机制将几何分析、热扩散和差分隐私联系起来

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学术论文,介绍了一种用于流形值数据的新颖隐私机制。
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Qirui Hu ·

    几何 Renyi 差分隐私:Ricci 曲率由热扩散机制表征

    In this paper, we develop a novel privacy mechanism for Riemannian manifold-valued data. Our key contribution lies in uncovering unexpected connections among geometric analysis, heat diffusion models, and differential privacy (DP). We characterize the Renyi divergence via dimensi…