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新算法在未知光滑区域实现线性收敛

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了新的算法，用于在算法未知光滑区域的情况下优化分段光滑（PWS）函数。对于满足二次增长（QG）条件的凸PWS函数，一种捆绑级别（BL）类型的方法实现了全局线性收敛，这是该问题类别中的首次突破。该方法已扩展到弱凸PWS问题，其复杂度与光滑非凸优化相匹配。此外，还引入了一个可验证的终止准则，该准则无需了解问题参数即可准确表征最优性差距。 AI

影响 为优化问题引入了新颖的算法方法，可能影响依赖于高效函数优化的AI研究。

排序理由 该集群包含一篇arXiv预印本，详细介绍了优化问题的新算法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新算法在未知光滑区域实现线性收敛

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该集群包含一篇arXiv预印本，详细介绍了优化问题的新算法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zhe Zhang, Suvrit Sra ·

    具有未知光滑区域的非光滑问题的线性收敛算法

    arXiv:2507.19465v2 Announce Type: replace-cross Abstract: We develop efficient algorithms for optimizing piecewise smooth (PWS) functions when their smooth regions are \emph{unknown} to the algorithm. For convex PWS functions satisfying a quadratic growth (QG) condition, we demon…

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