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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。所提出的近端线性算法基于时间平滑方法和近端残差映射,提供了一种实现一阶平稳性的方法。该算法的分析利用了切线锥特征来描述由复合差分凸约束定义的が可能な区域,从而可以通过凸优化预言机进行更新。该工作还建立了局部遗憾界限和内部凸子问题数量的界限,以及近似平稳性的误差界限。 AI

排序理由 该集群包含一篇在 arXiv 上发表的研究论文,详细介绍了一种用于优化问题的新算法。[lever_c_demoted from research: ic=1 ai=0.4]

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 →

新算法解决复杂的非凸优化问题

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该集群包含一篇在 arXiv 上发表的研究论文,详细介绍了一种用于优化问题的新算法。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jingwei Ji, Jong-Shi Pang, Renyuan Xu ·

    光滑映射下凸差组合的在线优化

    arXiv:2607.19553v1 Announce Type: cross Abstract: 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 constrain…