English(EN) New Accelerated Past-Extragradient Methods with Variance Reduction for Generalized Equations

新型加速算法提高了广义方程的收敛性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

研究人员开发了一个新的算法框架，该框架结合了Nesterov加速和方差缩减技术来解决一类广义方程。该方法专为涉及非单调算子的数据驱动应用而设计，与非加速方法相比，收敛速度得到了提高。该框架支持各种随机方差缩减方案，并在数值示例中表现出有希望的性能。 AI

影响改进了数据驱动应用中使用的优化算法的理论基础。

排序理由该集群包含一篇详细介绍新颖算法方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

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arXiv stat.ML TIER_1 English(EN) · Quoc Tran-Dinh, Nghia Nguyen-Trung · 2026-09-10 04:00

广义方程的新型加速近端-超梯度方法及方差缩减技术

arXiv:2508.16791v2 Announce Type: replace-cross Abstract: We develop a novel past-extragradient-type algorithmic framework, combining both Nesterov's \textit{acceleration} and \textit{variance-reduction} techniques, to solve a class of generalized equations involving possibly \te…