English(EN) Efficient Parameter Estimation of Truncated Boolean Product Distributions

研究人员探索截断布尔积分布的高效参数估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-05 04:00

研究人员开发了一种估计截断布尔积分布参数的新方法，该问题此前在离散环境中未得到解决。该方法依赖于截断集的“肥度”概念，该概念决定是否揭示了足够的信息来执行统计任务。这项工作表明，如果截断集足够肥且可通过查询访问，则仅需略微增加样本复杂度即可高效地执行标准统计任务。 AI

影响引入了从不完整数据中学习的新颖统计技术，可能适用于AI中的复杂离散模型。

排序理由这是一篇发表在arXiv上的研究论文，详细介绍了一种新的统计方法。[lever_c_demoted from research: ic=1 ai=1.0]

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

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arXiv stat.ML TIER_1 English(EN) · Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos · 2026-05-05 04:00

截断布尔积分布的高效参数估计

arXiv:2007.02392v3 Announce Type: replace-cross Abstract: We study the problem of estimating the parameters of a Boolean product distribution in $d$ dimensions, when the samples are truncated by a set $S \subset \{0, 1\}^d$ accessible through a membership oracle. This is the firs…