2021
DOI: 10.48550/arxiv.2108.00219
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Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization

Wentao Zhang,
Zhi Yang,
Yexin Wang
et al.

Abstract: Data selection methods, such as active learning and core-set selection, are useful tools for improving the data efficiency of deep learning models on large-scale datasets. However, recent deep learning models have moved forward from independent and identically distributed data to graph-structured data, such as social networks, ecommerce user-item graphs, and knowledge graphs. This evolution has led to the emergence of Graph Neural Networks (GNNs) that go beyond the models existing data selection methods are de… Show more

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