English(EN) Boosting and the Expressive Power of Simple Weak Learners via the $γ$-VC Dimension

新 $γ$-VC 维度参数用于分析弱学习器提升

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 16:42

本文介绍并分析了 $γ$-VC 维度，这是一个表征将弱假设转化为精确预测器所需样本复杂度的参数。该研究细化了传统 VC 维度与此新参数之间的关系。此外，它还提供了关于 $\mathbb{R}^d$ 中决策桩和轴平行矩形 $γ$-VC 维度的更新的上限和下限。 AI

影响引入了一个新的参数来分析弱学习器的表达能力，有可能加深对提升算法的理解。

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-10-07 16:42

通过 $γ$-VC 维度提升简单弱学习器的表达能力

Boosting converts weak hypotheses with a small edge over random guessing into highly accurate predictors, but the expressive power of the resulting classifier can depend strongly on the structure of the base class. We study this phenomenon through the $γ$-VC dimension introduced …