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cs.LG2024
Soft Label PU Learning
Yong Lei, Puning Zhao, Jintao Deng +1
PU learning refers to the classification problem in which only part of positive samples are labeled. Existing PU learning methods treat unlabeled samples equally. However, in many…
cs.NE2024
MemFlow: A Lightweight Forward Memorizing Framework for Quick Domain Adaptive Feature Mapping
Jianming Lv, Chengjun Wang, Depin Liang +3
Deploying pretrained visual models in real-world environments often suffers from significant performance degradation due to the diversity of testing scenarios. Continuous adaptatio…