English(EN) Why $\beta_1 = \beta_2$ Is Dynamically Special in Adam

Adam 优化器的绑定动量参数揭示了独特的训练动态

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-18 04:00

一篇新发表在 arXiv 上的论文探讨了 Adam 优化器的动态，Adam 是大规模 AI 训练的核心组件。该研究识别出与其两个动量参数 $\beta_1$ 和 $\beta_2$ 相关的特定机制。研究表明，当这些参数绑定时（$\beta_1 = \beta_2$），更新坐标中的滞后项会消失，从而导致以符号为主的更新和更平滑的训练轨迹。这一发现为绑定动量配置为何具有动态独特性并能保持强劲性能提供了机制性解释。 AI

影响提供了对训练大规模 AI 模型至关重要的优化技术的更深入理解。

排序理由该集群包含一篇详细介绍 AI 优化算法新发现的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

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arXiv stat.ML TIER_1 English(EN) · Alberto Fern\'andez-Hern\'andez, Cristian P\'erez-Corral, Jose I. Mestre, Manuel F. Dolz, Enrique S. Quintana-Ort\'i · 2026-09-18 04:00

Adam 中为何 $\beta_1 = \beta_2$ 在动态上很特别

arXiv:2601.21739v3 Announce Type: replace-cross Abstract: Adam has been at the core of large-scale training for almost a decade, yet the role of its two momentum parameters remains poorly understood. Recent work shows that tying $\beta_{1}=\beta_{2}$ can preserve Adam's strong pe…

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报道来源 [1]

Adam 中为何 $\beta_1 = \beta_2$ 在动态上很特别

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