conference-paper
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Data-Efficient Graph Learning
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Paper overview
Abstract
My research strives to develop fundamental graph-centric learning algorithms to reduce the need for human supervision in low-resource scenarios. The focus is on achieving effective and reliable data-efficient learning on graphs, which can be summarized into three facets: (1) graph weakly-supervised learning; (2) graph few-shot learning; and (3) graph self-supervised learning.
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Publication details
- DOI
- 10.1609/aaai.v38i20.30279
- OpenAlex
- W4393160701
- Document type
- conference-paper
- Language
- EN
- Source
- Proceedings of the AAAI Conference on Artificial Intelligence
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