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cs.CV2025★ 1 cited
Efficient Adaptive Label Refinement for Label Noise Learning
Wenzhen Zhang, Debo Cheng, Guangquan Lu +3
Deep neural networks are highly susceptible to overfitting noisy labels, which leads to degraded performance. Existing methods address this issue by employing manually defined crit…
cs.CV2017★ 2 cited
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction
Yanwei Pang, Bo Zhou, Feiping Nie
Explicitly or implicitly, most of dimensionality reduction methods need to determine which samples are neighbors and the similarity between the neighbors in the original highdimens…