English(EN) An Optimal Control Approach To Transformer Training

揭示Transformer训练新最优控制理论

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-23 04:00

研究人员开发了一种新颖的Transformer训练最优控制理论框架。该方法将Transformer架构建模为表现出McKean-Vlasov动力学的受控粒子系统，可以提升为完全可观测的马尔可夫决策过程。该方法确立了全局最优策略的存在性，并提出了一种提升的MDP的三重量化训练程序，为基于梯度的训练提供了一种理论上稳健的替代方案。 AI

影响引入了Transformer训练的新理论框架，可能为当前基于梯度的方法提供一种稳健的替代方案。

排序理由详细介绍Transformer模型训练新理论方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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Newsworthiness bucket: Tool; 详细介绍Transformer模型训练新理论方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Ka\u{g}an Akman, Naci Saldi, Serdar Y\"uksel · 2026-10-23 04:00

An Optimal Control Approach To Transformer Training

arXiv:2603.09571v2 Announce Type: replace Abstract: In this paper, we develop a rigorous optimal control-theoretic approach to Transformer training that respects key structural constraints such as (i) realized-input-independence during execution, (ii) the ensemble control nature …

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An Optimal Control Approach To Transformer Training

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