PARA 发表于 2025-3-30 10:28:18
http://reply.papertrans.cn/24/2343/234273/234273_51.pnggruelling 发表于 2025-3-30 16:06:09
https://doi.org/10.1007/978-1-349-19749-1active learning, or DAST-AL framework, that looks ahead the effect of ISDA in the selection of unlabeled samples. Specifically, DAST-AL exploits expected partial model change maximization (EPMCM) to consider selected samples’ potential contribution of the diversity to the labeled set by leveraging tdictator 发表于 2025-3-30 18:13:41
http://reply.papertrans.cn/24/2343/234273/234273_53.png使虚弱 发表于 2025-3-30 22:04:29
Investment and Technology Choice us to consider the classes (which are already labeled) as the varying environments (The word “environments” [.] denotes the subsets of training data built by some criteria. In this paper, we take a class as an environment—our key idea.) to resolve context bias (without context labels). We implement过分自信 发表于 2025-3-31 04:47:08
http://reply.papertrans.cn/24/2343/234273/234273_55.png染色体 发表于 2025-3-31 07:26:27
http://reply.papertrans.cn/24/2343/234273/234273_56.pngEstimable 发表于 2025-3-31 10:14:40
Investment and Technology Choicen generative models for the target task. We demonstrate the effectiveness of RealPatch on three benchmark datasets, CelebA, Waterbirds and a subset of iWildCam, showing improvements in worst-case subgroup performance and in subgroup performance gap in binary classification. Furthermore, we conduct e哎呦 发表于 2025-3-31 15:09:19
http://reply.papertrans.cn/24/2343/234273/234273_58.pngSubstitution 发表于 2025-3-31 20:30:10
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