Generalization bounds for graph convolutional neural networks via Rademacher complexity
收藏DataCite Commons2026-01-07 更新2026-05-05 收录
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https://service.tib.eu/ldmservice/dataset/8a0f07f4-59af-4af1-9af8-0fdc0bac4630
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资源简介：
This paper aims at studying the sample complexity of graph convolutional neural networks (GCNs), by providing tight upper bounds of Rademacher complexity for GCN models with a single hidden layer.
提供机构：
TIB
创建时间：
2024-12-16
