A Hybrid Adaptive Sampling Strategy for Fair and Accurate Meta-learned User Modeling.
Zheng Zhang|Qi Liu|Zirui Hu|Yi Zhan|Zhenya Huang|Weibo Gao|Qingyang Mao|Enhong Chen
| Anthology ID: | DBLP:journals/tois/ZhangLHZHGMC26 |
|---|---|
| Year: | 2026 |
| Venue: | ACM Transactions on Information Systems (TOIS) |
| Pages: | 24:1-24:39 |
| URL: | https://doi.org/10.1145/3769296 |
| DOI: | https://doi.org/10.1145/3769296 |
| DBLP: | journals/tois/ZhangLHZHGMC26 |
| BibTeX: |
@article{zhang-2026-hybrid,
author = {Zheng Zhang and
Qi Liu and
Zirui Hu and
Yi Zhan and
Zhenya Huang and
Weibo Gao and
Qingyang Mao and
Enhong Chen},
title = {{A Hybrid Adaptive Sampling Strategy for Fair and Accurate Meta-learned User Modeling}},
journal = {ACM Transactions on Information Systems (TOIS)},
volume = {44},
number = {1},
pages = {24:1--24:39},
year = {2026},
url = {https://doi.org/10.1145/3769296},
doi = {https://doi.org/10.1145/3769296}
}