The paper derives transductive generalization bounds for Lipschitz graph learners, including GCNs, on a single graph, with O(N^{-1/2}) rates in the number of labeled nodes.
Failures of model-dependent generalization bounds for least-norm interpolation.Journal of Machine Learning Research, 22(204):1–15, 2021
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Learning from one graph: transductive learning guarantees via the geometry of small random worlds
The paper derives transductive generalization bounds for Lipschitz graph learners, including GCNs, on a single graph, with O(N^{-1/2}) rates in the number of labeled nodes.