New analytic method characterizes kernel regression generalization error

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-09 04:00

研究人员开发了一种新的解析函数参数，用于严格表征核梯度下降和其他谱算法的泛化误差曲线。该方法在各种条件下，包括源条件、噪声水平和正则化参数，全面理解泛化误差。研究结果通过利用神经切线核理论的见解，显著改进了对宽神经网络泛化行为的理解。 AI

影响提供了对神经网络泛化更深入的理论理解，可能指导未来的模型开发。

排序理由这是一篇研究论文，详细介绍了一种理解机器学习算法泛化误差的新解析方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Yicheng Li, Weiye Gan, Zuoqiang Shi, Qian Lin · 2026-06-09 04:00

Analytic Spectral Algorithms under Power-law Decay 的泛化误差曲线

arXiv:2401.01599v4 Announce Type: replace Abstract: The generalization error curve of certain kernel regression method aims at determining the exact order of generalization error with various source condition, noise level and choice of the regularization parameter rather than the…