English(EN) Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions

大型维度下的谱算法揭示了三种学习曲线模式

作者 PulseAugur 编辑部 · [2 个来源] · 2026-04-25 08:38

一篇新发表在arXiv上的研究论文探讨了大型维度设置下谱算法的学习曲线和良性过拟合现象。该研究描述了不同正则化路径下的超额风险，确定了三种不同的模式：过度正则化、欠正则化和插值。在与回归函数平滑度相关的特定条件下，良性过拟合发生在后两种模式中。 AI

影响为谱算法的行为提供了理论见解，可能为未来的模型开发和分析提供信息。

排序理由发表在arXiv上的学术论文，详细介绍了机器学习领域的理论发现。

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arXiv stat.ML TIER_1 English(EN) · Weihao Lu, Qian Lin, Yingcun Xia, Dongming Huang · 2026-04-28 04:00

高维谱算法的学习曲线与良性过拟合

arXiv:2604.23212v1 Announce Type: new Abstract: Existing large-dimensional theory for spectral algorithms resolves either the optimally tuned point or the interpolation limit, but leaves the under-regularized regime unexplored. We study the learning curve and benign overfitting o…
arXiv stat.ML TIER_1 English(EN) · Dongming Huang · 2026-04-25 08:38

高维谱算法的学习曲线与良性过拟合

Existing large-dimensional theory for spectral algorithms resolves either the optimally tuned point or the interpolation limit, but leaves the under-regularized regime unexplored. We study the learning curve and benign overfitting of spectral algorithms in the large-dimensional s…