Gradient Coordination for Quantifying and Maximizing Knowledge Transference in Multi-Task Learning.
Xuanhua Yang|Jianxin Zhao|Shaoguo Liu|Liang Wang|Bo Zheng
| Anthology ID: | DBLP:conf/sigir/YangZLWZ23 |
|---|---|
| Volume: | Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023 |
| Year: | 2023 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2032-2036 |
| URL: | https://doi.org/10.1145/3539618.3591993 |
| DOI: | https://doi.org/10.1145/3539618.3591993 |
| DBLP: | conf/sigir/YangZLWZ23 |
| BibTeX: |
@inproceedings{yang-2023-gradient,
author = {Xuanhua Yang and
Jianxin Zhao and
Shaoguo Liu and
Liang Wang and
Bo Zheng},
editor = {Hsin-Hsi Chen and
Wei-Jou (Edward) Duh and
Hen-Hsen Huang and
Makoto P. Kato and
Josiane Mothe and
Barbara Poblete},
title = {{Gradient Coordination for Quantifying and Maximizing Knowledge Transference in Multi-Task Learning}},
booktitle = {{Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023}},
pages = {2032--2036},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3539618.3591993},
doi = {https://doi.org/10.1145/3539618.3591993}
}