Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks.
Zihan Luo|Jianxun Lian|Hong Huang|Hai Jin|Xing Xie
| Anthology ID: | DBLP:conf/wsdm/LuoL00022 |
|---|---|
| Volume: | WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022 |
| Year: | 2022 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 638-647 |
| URL: | https://doi.org/10.1145/3488560.3498460 |
| DOI: | https://doi.org/10.1145/3488560.3498460 |
| DBLP: | conf/wsdm/LuoL00022 |
| BibTeX: |
@inproceedings{luo-2022-adagnn,
author = {Zihan Luo and
Jianxun Lian and
Hong Huang and
Hai Jin and
Xing Xie},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {638--647},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3498460},
doi = {https://doi.org/10.1145/3488560.3498460}
}