Practical Single Domain Generalization via Training-time and Test-time Learning-Reference-Cited by-同舟云学术

Practical Single Domain Generalization via Training-time and Test-time Learning

Published:2024-08-24 Issue: Volume:151 Page:3794-3805
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Yang Shuai¹^ORCID,Zhang Zhen¹^ORCID,Gu Lichuan¹^ORCID

Affiliation:

1. School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, Anhui, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671806

Reference44 articles.

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2. Liang Chen, Yong Zhang, Yibing Song, Ying Shan, and Lingqiao Liu. 2023. Improved Test-Time Adaptation for Domain Generalization. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, June 17--24. 24172--24182.

3. Liang Chen, Yong Zhang, Yibing Song, Jue Wang, and Lingqiao Liu. 2022. OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training. In Advances in Neural Information Processing Systems, New Orleans, LA, USA, November 28 - December 9. 1--12.

4. Seokeon Choi, Debasmit Das, Sungha Choi, Seunghan Yang, Hyunsin Park, and Sungrack Yun. 2023. Progressive Random Convolutions for Single Domain Generalization. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, June 17--24. 10312--10322.

5. Stable learning establishes some common ground between causal inference and machine learning