VC-维度的几何分类器在主动学习中的应用

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

本文通过计算各种几何空间中度量球分类器的VC维，深入探讨了几何机器学习中泛化的理论基础。它在欧几里得、球面和双曲几何以及一般的范数向量空间和黎曼流形中为这些分类器建立了界限。研究还利用覆盖论证来探索高维欧几里得空间低维子集上数据的泛化界限，并特别应用于主动学习算法。 AI

影响为几何机器学习中的泛化提供了理论界限，可能改进主动学习算法。

排序理由该集群包含一篇详细介绍机器学习理论研究的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Gokul Bhusal, Delanna Do, Ekaterina Merkurjev, Kevin Miller, Stephan Wojtowytsch · 2026-11-11 05:00

VC-Dimension and Generalization in Geometric Machine Learning with Applications to Active Learning

arXiv:2611.13337v1 Announce Type: cross Abstract: We compute the VC-dimension of metric ball classifiers in the model spaces of Riemannian geometry (Euclidean, spherical, hyperbolic) and present upper and lower bounds on the VC-dimension of metric balls in several other situation…