English(EN) Random Parameter Noise Does Not Make Exact ReLU Verification Easy

随机噪声并不能简化精确 ReLU 网络验证

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-15 21:26

一篇新的研究论文探讨了在对抗性平滑下验证整流线性单元 (ReLU) 神经网络的复杂性。研究表明，添加随机参数噪声、裁剪和舍入网络权重并不能简化精确验证过程。研究结果表明，假设 NP 不是 BPP 的子集，即使对于某些网络配置存在固定的噪声水平，也不存在所有基本实例的高效验证器。 AI

影响这项研究表明，对抗性平滑技术可能无法为神经网络的高效验证提供一条直接的途径。

排序理由该集群包含一篇讨论理论计算机科学和神经网络验证的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Mojtaba Soltanalian · 2026-07-17 04:00

随机参数噪声并不能使精确 ReLU 验证变得容易

arXiv:2607.14375v1 Announce Type: cross Abstract: We study exact verification of ReLU networks in an adversarial smoothed model. Every network weight and bias is independently perturbed by Gaussian noise, clipped to $[-2,2]$, and rounded to the exact dyadic grid determined by the…
Hugging Face Daily Papers TIER_1 English(EN) · 2026-07-15 21:26

随机参数噪声并不能使精确 ReLU 验证变得容易

We study exact verification of ReLU networks in an adversarial smoothed model. Every network weight and bias is independently perturbed by Gaussian noise, clipped to $[-2,2]$, and rounded to the exact dyadic grid determined by the input bit complexity. We show that, under the sta…