English(EN) Reproducing Kernel (Quasi-)Banach Spaces with the $\ell^p$ Coefficient Norms

新理论探索具有 $\ell^p$ 范数的再生核空间

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

本文介绍了一个使用 $\ell^p$ 拟范数重现核拟巴拿赫空间（RKQBSs）的理论框架，特别关注 $01$，本文构建了具有固定字典的 RKBSs，并确定了一个最优的松弛表示因子。进行了数值实验，以比较不同 $p$ 情况下的准确性和稀疏性。 AI

影响推动了机器学习中核方法和稀疏性理论理解的进步。

排序理由这是一篇在 arXiv 上发表的理论计算机科学论文，详细介绍了机器学习理论方面的数学进展。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

$新理论探索具有 $\ell^p$ 范数的再生核空间$

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arXiv cs.LG TIER_1 English(EN) · Tianfang Wang, Guohui Song, Haizhang Zhang · 2026-11-06 05:00

用 $\ell^p$ 系数范数重现核（拟）巴拿赫空间

arXiv:2611.08032v1 Announce Type: new Abstract: This paper advances the theory of reproducing kernel Banach spaces (RKBSs) by investigating the general $\ell^p$ regularization framework, with a particular focus on the non-convex regime $0<p><1$. While our preceding work establish…