论文笔记：LCLR 2018 FastGCN: Fast Learning With Graph Convolutional Networks Via Important Sampling
前言 这篇文章对数学的要求好高，奈何自己水平有限读不太懂，想进一步了解的推荐去看原文或者后面附上的博客链接，此篇博客仅仅是作者按照自己的思考过程整理而得 作者基于2017年由Kipf和Welling提出的以一阶切比雪夫不等式为卷积核的图卷积算法，分析它的一些特点如下： 传统的GCN是一种直推式图卷积(Transductive learning)，也就是训练数据包含训练数据和测试数据，只是测试数据在
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相关文章
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