新研究探讨Banach空间中的最小范数插值

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-27 04:00

研究人员发表了一篇论文，在Banach空间背景下探讨了最小范数插值器（MNI）框架，特别关注了2-一致凸性的作用。这一假设比要求范数由内积诱导的限制性更小，通常意味着MNI没有封闭形式的解。该研究在此条件下为线性和非线性模型建立了MNI偏差的上限。论文证明，对于具有特定协变量分布的过参数化线性回归，该界限是尖锐的；当p在一定范围内且协变量非高斯时，也证明了$\ell_p$-MNI的尖锐泛化界限。 AI

影响为过参数化模型的泛化界限提供了理论见解，可能影响未来的模型开发。

排序理由关于理论机器学习框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Gil Kur, Pierre Bizeul · 2026-07-27 04:00

通过Banach空间局部理论实现最小范数插值：$2$-一致凸性的作用

arXiv:2603.28956v2 Announce Type: replace-cross Abstract: The minimum-norm interpolator (MNI) framework has recently attracted considerable attention as a tool for understanding generalization in overparameterized models, such as neural networks. In this work, we study the MNI un…

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通过Banach空间局部理论实现最小范数插值：$2$-一致凸性的作用

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