English(EN) Convergence Analysis of STORM Under Different Geometries

STORM优化算法在不同几何形状下的收敛性分析

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-03 04:00

本文对随机递归动量（STORM）优化算法的收敛性进行了分析。作者探讨了STORM在各种几何条件下的性能，特别是在不满足标准平均平滑度假设的情况下。他们为非凸、凸和强凸目标推导了新的收敛率，证明了STORM在这些场景下具有最优或接近最优的收敛率。 AI

排序理由该条目是一篇学术论文，详细介绍了优化算法的理论收敛性分析。[lever_c_demoted from research: ic=1 ai=0.4]

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本文如何被排名

Signal score: 2 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该条目是一篇学术论文，详细介绍了优化算法的理论收敛性分析。[lever_c_demoted from research: ic=1 ai=0.4]
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arXiv cs.LG TIER_1 English(EN) · Wei Jiang, Yibo Wang, Wenhao Yang, Rui Yan, Lijun Zhang, Zechao Li · 2026-10-03 04:00

不同几何形状下STORM的收敛性分析

arXiv:2610.01599v1 Announce Type: cross Abstract: Stochastic recursive momentum (STORM) achieves fast convergence for nonconvex optimization via the variance reduction effect, but existing analyses rely on the strong average smoothness assumption. In this paper, we study the conv…