Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation.
Weizhi Zhang|Liangwei Yang|Zihe Song|Henry Peng Zou|Ke Xu|Liancheng Fang|Philip S. Yu
| Anthology ID: | DBLP:conf/cikm/0001YSZXFY24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 3248-3258 |
| URL: | https://doi.org/10.1145/3627673.3679773 |
| DOI: | https://doi.org/10.1145/3627673.3679773 |
| DBLP: | conf/cikm/0001YSZXFY24 |
| BibTeX: |
@inproceedings{zhang-2024-really,
author = {Weizhi Zhang and
Liangwei Yang and
Zihe Song and
Henry Peng Zou and
Ke Xu and
Liancheng Fang and
Philip S. Yu},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {3248--3258},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679773},
doi = {https://doi.org/10.1145/3627673.3679773}
}