most citedLearning with Imbalanced Noisy Data by Preventing Bias in Sample Selection

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cs.CV2024

Foster Adaptivity and Balance in Learning with Noisy Labels

Mengmeng Sheng, Zeren Sun, Tao Chen +3

Label noise is ubiquitous in real-world scenarios, posing a practical challenge to supervised models due to its effect in hurting the generalization performance of deep neural netw…