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English(EN) Matching Multi-Loop Complexities with a Single Loop: Optimal Optimization Stationarity and Best-Known Game Stationarity in Nonconvex--Concave Minimax Optimization

新的单循环算法在优化中匹配多循环复杂度

研究人员引入了一种新颖的单循环算法框架,用于光滑的非凸-凹极大极小优化。这种新方法,称为投影阻尼外梯度法,集成了投影外梯度更新、对偶动量和移动近端中心。它在单循环一阶方法中的优化平稳性和博弈平稳性标准方面均达到了最佳已知复杂度,与多循环方法的性能相当。 AI

影响 这项研究推进了与训练复杂AI模型相关的优化技术。

排序理由 该条目是一篇在arXiv上发表的学术论文,详细介绍了一种新的优化算法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

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

新的单循环算法在优化中匹配多循环复杂度

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该条目是一篇在arXiv上发表的学术论文,详细介绍了一种新的优化算法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Minghao Zhang, Zi Xu ·

    用单个循环匹配多循环复杂度:非凸-凹最小极大优化中的最优优化平稳性和最佳已知博弈平稳性

    arXiv:2609.17973v1 Announce Type: cross Abstract: We introduce a new single-loop algorithmic framework for smooth nonconvex--concave minimax optimization. The resulting projected damped extragradient method combines projected extragradient updates, dual momentum, and a moving pro…