Domain generalization results (%) in the low-data regime with a comparison of various models in SSDG settings, evaluated on all datasets. Results are reported as mean ± standard deviation over 5 random seeds. Here, u denotes utilization of unlabeled data. Paired t-tests were conducted between CAT and other baselines, with p-values shown in the last row.

Domain generalization results (%) in the low-data regime with a comparison of various models in SSDG settings, evaluated on all datasets. Results are reported as mean ± standard deviation over 5 random seeds. Here, u denotes utilization of unlabeled data. Paired t-tests w...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Sumaiya Zoha (22184571) (author)
مؤلفون آخرون:	Jeong-Gun Lee (2048551) (author), Young-Woong Ko (22184574) (author)
منشور في:	2025
الموضوعات:	Biochemistry Microbiology Cell Biology Space Science Biological Sciences not elsewhere classified limited labeled data labeled source data multiple source domains learn robust representations 90 %</ b 47 %</ b 45 %</ b quality labeled data achieving robust generalization unseen target domains higher class diversity div >< p refining noisy pseudo supervised domain generalization combines adaptive thresholding cat </ b unseen domains domain generalization quality pseudo noisy pseudo supervised learning aware adaptive domain shifts robust semi pacs </ officehome </ minidomainnet </ transfer knowledge superior performance previous approaches often costly fixed thresholds extensive experiments efficient paradigm diverse set challenging problem
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