失去了共融,失去了规律性,以及不同的隐私.
March Boedihardjo1, Thomas Strohmer2, Roman Vershynin3
1Department of Mathematics, Michigan State University, East Lansing, USA.
概括
随机圆技术在有条件预期中为共变率损失设定了近乎紧密的边界. 这推进了矩阵和内核的弱规律定理,使得差别私有合成数据生成成为可能.
科学领域:
- 数学 数学 是一个数学.
- 计算机科学 计算机科学
- 统计 统计 统计 统计
背景情况:
- 共差损失量化了有条件预期中的信息减少.
- 随机圆是一种在近似算法中使用的技术.
- 施梅雷迪正则性定理在图形理论和组合学中是基本的.
研究的目的:
- 使用随机圆的方法,确定共变率损失的近乎紧密的边界.
- 介绍一个新的弱Szemeredi规律定理为正半确矩阵和内核.
- 探索该方法在构建差异性私有合成数据中的应用.
主要方法:
- 基于Grothendieck的身份的随机圆的应用.
- 开发了一个新的弱的Szemeredi规律定理.
- 为了生成合成数据,利用参数.
主要成果:
- 一个几乎紧密结合的共变量损失被证明.
- 建立了一种新型的弱Szemeredi规律定理,用于正半确矩阵和内核.
- 该方法被证明可以用于创建差异私有合成数据.
结论:
- 随机圆为分析协方差损失提供了一个强大的工具.
- 开发的正规性定理提供了新的理论见解.
- 这种方法有助于创建保护隐私的合成数据集.
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