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SLGAT: Soft Labels Guided Graph Attention Networks
Graph convolutional neural networks have been widely studied for semi-supervised classification on graph-structured data in recent years. They usually learn node representations by transforming, propagating, aggregating node features and minimizing the prediction loss on labeled nodes. However, the...
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| Publicado no: | Advances in Knowledge Discovery and Data Mining |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7206162/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47426-3_40 |
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