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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 231–240 of 249 papers

TitleStatusHype
Learning with Noisy Labels for Sentence-level Sentiment Classification—0
Symmetric Cross Entropy for Robust Learning with Noisy LabelsCode0
Deep Self-Learning From Noisy Labels—0
SELFIE: Refurbishing Unclean Samples for Robust Deep LearningCode0
Are Anchor Points Really Indispensable in Label-Noise Learning?Code0
Learning to Detect and Retrieve Objects from Unlabeled VideosCode0
A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels—0
Unifying semi-supervised and robust learning by mixup—0
Probabilistic End-to-end Noise Correction for Learning with Noisy LabelsCode0
Safeguarded Dynamic Label Regression for Generalized Noisy SupervisionCode0
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