Learning to Augment Imbalanced Data for Re-ranking Models.
Zi-Hao Qiu|Ying-Chun Jian|Qing-Guo Chen|Lijun Zhang
| Anthology ID: | DBLP:conf/cikm/QiuJCZ21 |
|---|---|
| Volume: | CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021 |
| Year: | 2021 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1478-1487 |
| URL: | https://doi.org/10.1145/3459637.3482364 |
| DOI: | https://doi.org/10.1145/3459637.3482364 |
| DBLP: | conf/cikm/QiuJCZ21 |
| BibTeX: |
@inproceedings{qiu-2021-learning,
author = {Zi-Hao Qiu and
Ying-Chun Jian and
Qing-Guo Chen and
Lijun Zhang},
editor = {Gianluca Demartini and
Guido Zuccon and
J. Shane Culpepper and
Zi Huang and
Hanghang Tong},
title = {{Learning to Augment Imbalanced Data for Re-ranking Models}},
booktitle = {{CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021}},
pages = {1478--1487},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3459637.3482364},
doi = {https://doi.org/10.1145/3459637.3482364}
}