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English(EN) Differentially Private Semantic Plans for Aggregate Insight Generation

新的DP-SPIN框架提供来自数据集群的私有聚合洞察

研究人员推出了一种名为DP-SPIN的新框架,该框架旨在为从数据相关集群中提取的聚合洞察提供差分隐私。此方法允许测量和汇总独立于受保护数据的语义概念。DP-SPIN生成一个差分隐私语义计划,语言模型可以使用该计划来检查概念提及和报告的值,从而在实现分析的同时确保隐私。该框架已在包括消费者投诉叙述和在线评论在内的各种数据集上针对记录级和用户级隐私进行了评估,证明了其与现有基线的有效性。 AI

影响 为AI应用的敏感数据集提供更私密、更具可扩展性的分析。

排序理由 该项目是一篇研究论文,详细介绍了一种用于聚合洞察生成的新差分隐私框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的DP-SPIN框架提供来自数据集群的私有聚合洞察

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该项目是一篇研究论文,详细介绍了一种用于聚合洞察生成的新差分隐私框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Behrooz Razeghi ·

    用于聚合洞察生成的差分隐私语义规划

    arXiv:2609.16283v1 Announce Type: new Abstract: \texttt{URANIA} provides end-to-end differential privacy (DP) for summaries of data-dependent clusters. However, its cluster--keyword release does not directly provide collection-wide aggregates for semantic concepts defined indepen…