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Tackling the Imbalance for GNNs
Different from deep neural networks for non-graph data classification, graph neural networks (GNNs) leverage the information exchange between nodes (or samples) when representing nodes.
A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off
Conducting a clear comparison for existing RML algorithms in dealing with different samples is difficult due to lack of a unified theoretical framework for RML.
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