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English(EN) Online Optimization of Difference-of-Convex Compositions with Smooth Mappings

新算法解决复杂的非凸优化问题

研究人员开发了一种用于复杂非凸问题在线优化新算法。所提出的时间平滑近邻线性算法解决了涉及光滑映射复合的差分凸函数问题。使用近邻残差映射分析了该算法的有效性,该映射作为问题的平稳性度量。尽管存在固有的非凸性,但这种方法允许通过凸优化预言机来计算更新。 AI

影响 为与机器学习相关的复杂优化问题引入了一种新的算法方法。

排序理由 该条目描述了研究论文中提出的一种新颖算法和理论分析。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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

新算法解决复杂的非凸优化问题

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该条目描述了研究论文中提出的一种新颖算法和理论分析。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    光滑映射下凸差组合的在线优化

    We study online optimization for a broad class of structured non-convex non-smooth problems where each loss is a composition of a difference-of-convex function with a smooth mapping, and the feasible region is defined by constraint functions of the same kind. We propose a time-sm…