A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data.
Wentao Wang|Harry Shomer|Yuxuan Wan|Yaxin Li|Jiangtao Huang|Hui Liu
| Anthology ID: | DBLP:conf/cikm/0006SWLHL23 |
|---|---|
| Volume: | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 |
| Year: | 2023 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 2637-2645 |
| URL: | https://doi.org/10.1145/3583780.3614762 |
| DOI: | https://doi.org/10.1145/3583780.3614762 |
| DBLP: | conf/cikm/0006SWLHL23 |
| BibTeX: |
@inproceedings{wang-2023-mixup,
author = {Wentao Wang and
Harry Shomer and
Yuxuan Wan and
Yaxin Li and
Jiangtao Huang and
Hui Liu},
editor = {Ingo Frommholz and
Frank Hopfgartner and
Mark Lee and
Michael P. Oakes and
Mounia Lalmas-Roelleke and
Min Zhang and
Rodrygo L. T. Santos},
title = {{A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {2637--2645},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3614762},
doi = {https://doi.org/10.1145/3583780.3614762}
}