Federated graph learning advances the field of federated learning by enabling privacy-preserving collaborative training on distributed graph data. Conventional federated graph learning methods excel ...
Abstract: COVID-19 prognosis using clinical tabular data faces significant challenges due to missing values and class imbalance issues. Existing methods often overlook the complex high-order ...
Abstract: Graph data, essential in fields like knowledge representation and social networks, often involves large networks with many nodes and edges. Transmitting these graphs can be highly ...
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