English(EN) Active Regression for Single-Index Models with Unknown Link Functions

新算法推进单指数模型的活跃回归

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-02 14:53

本文介绍了一种用于具有未知链接函数和一般$\ell_p$-损失的单指数模型的新型活跃回归算法。所提出的非自适应采样算法在特定的查询复杂度下实现了 $(1+ε)$-近似，解决了比先前工作更具挑战性的场景。该研究还为 $p>2$ 建立了近乎紧密的下界，显著缩小了这些模型中活跃 $\ell_p$-回归的差距。 AI

影响推进了单指数模型的理论理解和算法方法，可能在需要具有未知链接函数的回归的应用中提高性能。

排序理由该集群包含一篇详细介绍特定机器学习问题的新算法和理论界限的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-08-02 14:53

具有未知链接函数的单指标模型的活跃回归

This paper studies active regression for single-index models under general $\ell_p$-loss with an unknown $1$-Lipschitz link function $f$, formulated as $\min_{f,x} \|f(Ax)-b\|_p^p$ with full access to $A$ but coordinate-query access to $b$. Prior work established upper bounds for…

本文如何被排名

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具有未知链接函数的单指标模型的活跃回归

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