English(EN) Relaxed activation analysis of dataflow networks - A clock calculus for machine learning and real-time scheduling

为反应式应用中的机器学习提出新的时钟演算

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-27 04:00

研究人员提出了一种对Lustre时钟演算的扩展，以更好地在反应式应用中表示机器学习模型。这种新的演算解决了现有系统中的局限性，这些系统主要为嵌入式控制设计，难以处理ML训练算法中常见的复杂条件执行和递归状态。拟议的扩展旨在通过实现更有效的编译和更清晰地表示这些模式来促进ML模型的嵌入。 AI

影响这项研究可能能够更有效地将机器学习模型集成到实时反应式系统中。

排序理由学术论文在arXiv上发表，详细介绍了一种用于机器学习的新演算。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · William Gaudelier, Albert Cohen, Dumitru Potop Butucaru · 2026-07-27 04:00

数据流网络的松弛激活分析——用于机器学习和实时调度的时钟演算

arXiv:2607.21797v1 Announce Type: cross Abstract: Previous work has shown that the simple dataflow primitives of the Lustre language allow the natural, semantically unambiguous, and compact representation of machine learning (ML) applications, including models featuring complex c…