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English(EN) Tight list replicability bounds via a novel sphere covering theorem

球覆盖定理为学习理论可复现性提供严格界限

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新颖的球覆盖定理，该定理源自Borsuk-Ulam定理，用于确定学习理论中列表可复现性的严格界限。该新定理通过将列表大小与准确性参数和假设类复杂度相关联，有助于形式化可复现性。研究结果为VC类提供了精确的界限，并证明了用于大间隔半空间的最佳列表大小，在特定间隔条件下实现了最小列表大小。 AI

影响 为机器学习中的可复现性建立了新的理论界限，可能指导算法开发。

排序理由 该集群包含一篇详细介绍机器学习新理论结果的学术论文。

在 arXiv cs.LG 阅读 →

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球覆盖定理为学习理论可复现性提供严格界限

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Ari Blondal, Hamed Hatami, Pooya Hatami, Chavdar Lalov, Sivan Tretiak ·

    一种新颖的球覆盖定理带来的紧凑列表可复现性界限

    arXiv:2606.06148v1 Announce Type: new Abstract: In recent years, list replicability has emerged as a framework for formalizing reproducibility in learning theory. A central question is how the required list size relates to the accuracy parameter and natural complexity measures of…

  2. arXiv cs.LG TIER_1 English(EN) · Sivan Tretiak ·

    一种新颖的球覆盖定理带来的紧凑列表可复现性界限

    In recent years, list replicability has emerged as a framework for formalizing reproducibility in learning theory. A central question is how the required list size relates to the accuracy parameter and natural complexity measures of the hypothesis class. To achieve sharp bounds o…

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