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Learning with noisy labels

Learning with noisy labels means When we say "noisy labels," we mean that an adversary has intentionally messed up the labels, which would have come from a "clean" distribution otherwise. This setting can also be used to cast learning from only positive and unlabeled data.

Papers

Showing 181190 of 249 papers

TitleStatusHype
Prototypical Classifier for Robust Class-Imbalanced Learning0
Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African Languages0
Distilling effective supervision for robust medical image segmentation with noisy labels0
Does label smoothing mitigate label noise?0
Do We Need to Penalize Variance of Losses for Learning with Label Noise?0
DST: Data Selection and joint Training for Learning with Noisy Labels0
DualGraph: A Graph-Based Method for Reasoning About Label Noise0
Randomized Wagering Mechanisms0
Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples0
RankMatch: Fostering Confidence and Consistency in Learning with Noisy Labels0
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