English(EN) Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming

开发了新的欧几里得约旦代数差分隐私机制

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-11 05:00

研究人员开发了一种新的通用高斯机制，用于欧几里得约旦代数内的差分隐私计算。该框架适用于各种数学结构，包括线性规划、二阶锥规划和半定规划的基础结构。该工作为对称锥规划引入了差分隐私算法，特别解决了 2014 年 ICALP 论文中关于差分隐私半定规划的一个悬而未决的问题。 AI

影响这项研究推进了隐私保护优化技术（privacy-preserving optimization techniques）的理论基础，可能影响未来需要复杂数学运算中强大数据保护的 AI 系统。

排序理由该集群包含一篇学术论文，详细介绍了数学和计算机科学专业领域的一种新理论方法。[lever_c_demoted from research: ic=1 ai=0.7]

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arXiv cs.LG TIER_1 English(EN) · Zhao Song, Jianfei Xue, Lichen Zhang · 2026-11-11 05:00

欧几里得约旦代数的差分隐私及其在私有对称锥规划中的应用

arXiv:2509.16915v2 Announce Type: replace-cross Abstract: In this paper, we study differentially private mechanisms for functions whose outputs lie in a Euclidean Jordan algebra. Euclidean Jordan algebras capture many important mathematical structures and form the foundation of l…