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cs.LG2023
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
Large-scale graph machine learning is challenging as the complexity of learning models scales with the graph size. Subsampling the graph is a viable alternative, but sampling on gr…
cs.LG2023
A Local Graph Limits Perspective on Sampling-Based GNNs
Yeganeh Alimohammadi, Luana Ruiz, Amin Saberi
We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable…