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Trustworthy DD · Gradient matching

Fair Graph Distillation

Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu

NeurIPS 2023 · first public 2023-01-01

paper ↗catalogued✓ abstract read

In one paragraph

Shows that GNNs trained on graphs condensed by existing graph-distillation methods can exhibit more severe group-fairness problems than GNNs trained on the original graph, then proposes a fair graph-distillation approach that generates small distilled graphs that are both fair and informative.

Where it sits

BibTeX (generated; prefer the venue's official entry)
@article{feng2023fair,
  title   = {Fair Graph Distillation},
  author  = {Qizhang Feng and Zhimeng Jiang and Ruiquan Li and Yicheng Wang and Na Zou and Jiang Bian and Xia Hu},
  journal = {NeurIPS 2023},
  year    = {2023}
}

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