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English(EN) Understanding Circulant Permutation to Extend the CMinHash Estimator

新方法扩展CMinHash算法以改进方差分析

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的方法来分析和扩展CMinHash算法，这是一种MinHash估计方法。这种新技术提供了明确且可比较的近似方差表达式，而这对于其他MinHash估计器来说之前很难推导。所提出的方法被用于分析Minner估计器，数值实验证实了推导出的方差表达式能够准确预测估计值的经验均方误差。这项工作为将循环排列应用于更广泛的MinHash估计器并计算其近似方差铺平了道路。 AI

影响 这项研究为分析和潜在改进用于大规模数据处理和相似性搜索的数据草图技术提供了一种更稳健的方法。

排序理由 该集群包含一篇详细介绍统计估计算法新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

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新方法扩展CMinHash算法以改进方差分析

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该集群包含一篇详细介绍统计估计算法新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Keegan Kang, Avery Hood, Benedict H. W. Wong ·

    理解循环置换以扩展CMinHash估计器

    arXiv:2610.18551v1 Announce Type: new Abstract: CMinHash promises a new direction for designing MinHash algorithms with reduced variance and storage space via circulant permutations. However, the original variance analysis is difficult to extend to other MinHash estimators. We pr…

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