研究人员开发了一种新的“杆流”模型，以更好地理解像Adam这样的自适应梯度优化方法在稳定性边缘的运行方式。该模型将之前关于梯度下降的工作扩展到包括基于动量的方法，将优化迭代视为一维“杆”。新框架准确地跟踪了包括Adam和RMSProp在内的八种不同优化器在各种机器学习架构上的离散迭代。 AI
影响 为理解和潜在地提高机器学习中常用优化算法的稳定性提供了更准确的理论框架。
排序理由 该集群包含一篇详细介绍优化算法新建模技术的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2605.06821v1 Announce Type: cross Abstract: Cohen et al. (arXiv:2207.14484) observed that adaptive gradient methods such as Adam operate at the edge of stability. While there has been significant work on continuous-time modeling of gradient descent at the edge of stability,…
Cohen et al. (arXiv:2207.14484) observed that adaptive gradient methods such as Adam operate at the edge of stability. While there has been significant work on continuous-time modeling of gradient descent at the edge of stability, extending these models to momentum methods remain…