English(EN) Learning and Testing Convex Functions

高斯空间上学习和测试凸函数的新算法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-15 04:00

研究人员开发了在高维高斯空间中学习和测试凸函数的新算法。所提出的Lipschitz凸函数的不可知 Proper 学习算法以\(\varepsilon\)的误差实现了\(n^{O(1/\\varepsilon^2)}\)的样本复杂度。作为补充，在相关统计查询（CSQ）模型中建立了\(n^{\\mathrm{poly}(1/\\varepsilon)}\)样本的下界。该工作还提出了一个具有相似样本复杂度的凸性容错测试器和一个需要\(O(\\sqrt{n}/\\varepsilon)^n\)样本的单侧测试器。 AI

排序理由该集群包含一篇研究论文，详细介绍了学习和测试凸函数的新算法和理论界限。[lever_c_demoted from research: ic=1 ai=0.7]

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arXiv cs.LG TIER_1 English(EN) · Renato Ferreira Pinto Jr., Cassandra Marcussen, Elchanan Mossel, Shivam Nadimpalli · 2026-07-15 04:00

学习和测试凸函数

arXiv:2511.11498v2 Announce Type: replace-cross Abstract: We consider the problems of \emph{learning} and \emph{testing} real-valued convex functions over Gaussian space. Despite the extensive study of function convexity across mathematics, statistics, and computer science, its l…

本文如何被排名

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学习和测试凸函数

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