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English(EN) XMSE-Aware Adaptive Empirical Bayes Estimation

新的 XMSE 感知混合估计器融合了机器学习和经验贝叶斯

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了一种新颖的 XMSE 感知混合估计器，该估计器在最大似然 (ML) 和经验贝叶斯 (EB) 收缩之间进行插值。该方法旨在改进现有的 EB 估计器，当其核与真实参数不对齐时，EB 估计器可能表现不如 ML。所提出的方法使用固定的 XMSE 来推导一个最优混合权重，确保其性能不劣于 ML 或基础 EB 估计器。基于有限样本 XMSE 近似的即插即用实现被证明是一致的，并提供了二阶最优遗憾率。 AI

影响 这项研究可能导致机器学习中更强大的统计方法，特别是在核错误指定的情况下。

排序理由 该集群描述了一篇关于统计估计方法的新学术论文。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

新的 XMSE 感知混合估计器融合了机器学习和经验贝叶斯

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报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Jiale Zheng ·

    XMSE感知自适应经验贝叶斯估计

    Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order: recent excess mean squared error (XMSE) analysis shows that kernel-based EB estimation may be worse than ML when the kernel is poo…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    XMSE感知自适应经验贝叶斯估计

    Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order: recent excess mean squared error (XMSE) analysis shows that kernel-based EB estimation may be worse than ML when the kernel is poo…

  3. arXiv stat.ML TIER_1 English(EN) · Minghao Chen, Jiale Zheng ·

    XMSE感知自适应经验贝叶斯估计

    arXiv:2606.26975v1 Announce Type: new Abstract: Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order: recent excess mean squared error (XMSE) analysis shows that kernel-based EB estima…

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