English(EN) Random Cloud: Finding Minimal Neural Architectures Without Training

Random Cloud 方法在无训练情况下寻找最小神经网络架构

作者 PulseAugur 编辑部 · [2 个来源] · 2026-04-29 15:57

一种名为Random Cloud的新型无训练方法被提出，用于发现最小的神经网络架构。该方法在最终训练前，利用随机初始化的网络进行随机探索和结构缩减，在多个基准测试中表现优于传统的剪枝方法。Random Cloud方法还通过避免训练全尺寸网络的需要，提供了显著的速度优势。 AI

影响提供了一种更快、更有效的方法来寻找最优的神经网络架构，有望降低人工智能开发的计算成本。

排序理由介绍一种新颖的神经架构搜索方法的学术论文。

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.AI TIER_1 English(EN) · Javier Gil Bl\'azquez · 2026-04-30 04:00

Random Cloud：在无需训练的情况下寻找最小神经网络架构

arXiv:2604.26830v1 Announce Type: cross Abstract: I propose the \emph{Random Cloud} method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies through stochastic exploration and progressive structural reduction. Unlike pos…
arXiv cs.AI TIER_1 English(EN) · Javier Gil Blázquez · 2026-04-29 15:57

Random Cloud：在无需训练的情况下寻找最小神经网络架构

I propose the \emph{Random Cloud} method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies through stochastic exploration and progressive structural reduction. Unlike post-training pruning methods that require a full tra…