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English(EN) Benign overfitting beyond prediction: The ordinary least squares interpolator

新研究探讨过参数化模型中的良性过拟合

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新研究论文探讨了过参数化统计模型中良性过拟合的现象，重点关注普通最小二乘（OLS）插值器。该研究为最小 $\ell_2$-范数 OLS 插值器推导了新的代数和统计结果，将重点从预测风险转移到参数估计和推断。主要贡献包括已建立的统计公式的过参数化类似物以及方差估计的分析，为理解过参数化线性模型中的参数估计提供了框架。 AI

影响 为理解过参数化模型提供了理论框架，可能为未来的 AI 发展提供信息。

排序理由 关于统计理论的学术论文。[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 →

新研究探讨过参数化模型中的良性过拟合

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关于统计理论的学术论文。[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) · Dennis Shen, Dogyoon Song, Peng Ding, Jasjeet S. Sekhon ·

    Benign overfitting beyond prediction: The ordinary least squares interpolator

    arXiv:2309.15769v3 Announce Type: replace-cross Abstract: Recent advances in deep learning have highlighted the phenomenon of benign overfitting in overparameterized statistical models, sparking significant interest in understanding its foundations. Owing to its simplicity and pr…

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