English(EN) Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy

新的minimax分位数理论增强了统计决策中的隐私保护

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-22 09:41

研究人员为交互式统计决策（ISDM）开发了一种新的minimax分位数理论，该理论解决了罕见但重大的失败，而传统的基于期望的标准（如minimax风险和遗憾）无法捕捉到这些失败。该理论建立了minimax分位数、下minimax分位数和minimax风险之间的结构关系，包括从分位数到期望的转换以及严格minimax分位数和下minimax分位数之间的等价性。该工作还为ISDM引入了反例工具，例如高概率交互式Fano方法和Le Cam方法，并展示了如何通过约束可容许决策类别将互信息隐私集成到此框架中。 AI

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-06-22 09:41

Minimax 分位数下界用于隐私保护的交互式统计决策制定

Minimax risk and regret are expectation-based criteria and do not capture rare but consequential failures. To address this concern, we develop a $δ$-explicit minimax-quantile theory for interactive statistical decision making (ISDM). We first provide structural relations between …

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Minimax 分位数下界用于隐私保护的交互式统计决策制定

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