English(EN) Characterizing the Discrete Geometry of ReLU Networks

新的理论发现表征了ReLU网络的几何结构

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-09 04:00

研究人员在ReLU网络的离散几何方面取得了新的理论发现，重点关注其连通性图。这些图将节点表示为线性区域，将边连接共享面的区域，其平均度上限为输入维度的两倍，与网络深度或宽度无关。此外，即使区域数量呈指数增长，图的直径也具有独立于输入维度的上限。这些理论结果已通过在合成和真实世界数据上训练的网络进行的实验得到验证。 AI

影响提供了对神经网络结构的更深层次的理论理解，可能有助于可解释性和优化。

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在 arXiv cs.LG 阅读 →

ReLU networks

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arXiv cs.LG TIER_1 English(EN) · Blake B. Gaines, Jinbo Bi · 2026-06-09 04:00

ReLU网络离散几何特征分析

arXiv:2606.07728v1 Announce Type: new Abstract: It is well established that ReLU networks define continuous piecewise-linear functions, and that their linear regions are polyhedra in the input space. These regions form a complex that fully partitions the input space. The way thes…

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ReLU网络离散几何特征分析

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