Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization-Reference-Cited by-同舟云学术

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Tong Yunze¹^ORCID,Yuan Junkun¹^ORCID,Zhang Min¹^ORCID,Zhu Didi¹^ORCID,Zhang Keli²^ORCID,Wu Fei¹^ORCID,Kuang Kun¹^ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Noah's Ark Lab, Huawei Technologies, Shenzhen, China

Funder

Shanghai AI Laboratory

National Natural Science Foundation of China

Zhejiang Province Natural Science Foundation

Zhejiang Province Science and Technology

the StarryNight Science Fund of Zhejiang University Shanghai Institute for Advanced Study

Young Elite Scientists Sponsorship Program by CAST

the Fundamental Research Funds for the Central Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599481

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5. Junbum Cha , Sanghyuk Chun , Kyungjae Lee , Han-Cheol Cho , Seunghyun Park , Yunsung Lee , and Sungrae Park . 2021 . SWAD: Domain Generalization by Seeking Flat Minima. In Advances in Neural Information Processing Systems (NeurIPS). Junbum Cha, Sanghyuk Chun, Kyungjae Lee, Han-Cheol Cho, Seunghyun Park, Yunsung Lee, and Sungrae Park. 2021. SWAD: Domain Generalization by Seeking Flat Minima. In Advances in Neural Information Processing Systems (NeurIPS).

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