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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

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Showing 11–20 of 249 papers

TitleStatusHype
Regularly Truncated M-estimators for Learning with Noisy LabelsCode1
Improving Medical Image Classification in Noisy Labels Using Only Self-supervised PretrainingCode1
Co-Learning Meets Stitch-Up for Noisy Multi-label Visual RecognitionCode1
FedNoisy: Federated Noisy Label Learning BenchmarkCode1
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label ConfigurationsCode1
Bayesian Optimization Meets Self-DistillationCode1
Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in MoviesCode1
Twin Contrastive Learning with Noisy LabelsCode1
Learning with Noisy labels via Self-supervised Adversarial Noisy MaskingCode1
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy LabelsCode1
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