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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 101110 of 249 papers

TitleStatusHype
Labeling Chaos to Learning Harmony: Federated Learning with Noisy LabelsCode0
Neighborhood Collective Estimation for Noisy Label Identification and CorrectionCode1
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision TransformerCode1
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionCode1
ProMix: Combating Label Noise via Maximizing Clean Sample UtilityCode1
Compressing Features for Learning with Noisy LabelsCode1
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels0
Protoformer: Embedding Prototypes for TransformersCode1
Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy LabelsCode1
To Aggregate or Not? Learning with Separate Noisy Labels0
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