English(EN) Ideal Paths for Approximating Logistic Gradient Descent Trajectories at Large Initialization

新研究详细介绍了具有大型初始化的逻辑梯度下降路径

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

一篇新论文探讨了逻辑梯度下降轨迹的几何近似，特别是在从大型预训练模型进行初始化时。该研究引入了一条由线性段组成的连续理想路径，其中包括一个负边距校正阶段，然后是最小边距增长。当初始化规模增加时，这种近似收敛于全批量逻辑梯度下降轨迹，并为峰值和累积训练损失提供了定量误差界和渐近公式。 AI

影响为模型训练动力学提供了理论见解，可能为未来的优化策略提供信息。

排序理由该集群包含一篇在 arXiv 上发表的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

本文如何被排名

Signal score: 7 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇在 arXiv 上发表的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Junjie Xiao, Huiwen Jia · 2026-10-07 04:00

Approximating Logistic Gradient Descent Trajectories at Large Initialization of Ideal Paths

arXiv:2610.04142v2 Announce Type: replace Abstract: Modern training on a new task often starts from a previously trained model rather than from scratch, raising the question of how this initialization affects the subsequent training trajectory. Classical implicit-bias results cha…