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Contrastive Learning Improves Model Robustness Under Label Noise.
CVPR Workshops, pp.2703-2708, (2021)
Deep neural network-based classifiers trained with the categorical cross-entropy (CCE) loss are sensitive to label noise in the training data. One common type of method that can mitigate the impact of label noise can be viewed as supervised robust methods; one can simply replace the CCE loss with a loss that is robust to label noise, or...More
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