Learning Hypersphere for Few-shot Anomaly Detection on Attributed Networks.
Qiuyu Guo|Xiang Zhao|Yang Fang|Shiyu Yang|Xuemin Lin|Dian Ouyang
| Anthology ID: | DBLP:conf/cikm/GuoZFY0O22 |
|---|---|
| Volume: | Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 635-645 |
| URL: | https://doi.org/10.1145/3511808.3557377 |
| DOI: | https://doi.org/10.1145/3511808.3557377 |
| DBLP: | conf/cikm/GuoZFY0O22 |
| BibTeX: |
@inproceedings{guo-2022-learning,
author = {Qiuyu Guo and
Xiang Zhao and
Yang Fang and
Shiyu Yang and
Xuemin Lin and
Dian Ouyang},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{Learning Hypersphere for Few-shot Anomaly Detection on Attributed Networks}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {635--645},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557377},
doi = {https://doi.org/10.1145/3511808.3557377}
}