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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 2130 of 249 papers

TitleStatusHype
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and CorrectionCode1
RONO: Robust Discriminative Learning With Noisy Labels for 2D-3D Cross-Modal RetrievalCode1
Instance-Dependent Noisy Label Learning via Graphical ModellingCode1
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence PenalizationCode1
Neighborhood Collective Estimation for Noisy Label Identification and CorrectionCode1
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision TransformerCode1
ProMix: Combating Label Noise via Maximizing Clean Sample UtilityCode1
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionCode1
Compressing Features for Learning with Noisy LabelsCode1
Protoformer: Embedding Prototypes for TransformersCode1
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