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learning-with-noisy-labels-on-cifar-10n-1

Document Text ClassificationLearning with noisy labels
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PaperCodeAccuracy (mean)ModelNameReleaseDate
ProMix: Combating Label Noise via Maximizing Clean Sample Utility✓ Link96.97ProMix2022-07-21
PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labels✓ Link96.17PSSCL2024-12-18
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels✓ Link96.01PGDF2021-12-02
Robust Training under Label Noise by Over-parameterization✓ Link95.28SOP+2022-02-28
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations✓ Link94.85ILL2023-05-22
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach✓ Link94.45CORES*2020-10-05
Early-Learning Regularization Prevents Memorization of Noisy Labels✓ Link94.43ELR+2020-06-30
Partial Label Supervision for Agnostic Generative Noisy Label Learning✓ Link91.97GNL2023-08-02
Early-Learning Regularization Prevents Memorization of Noisy Labels✓ Link91.46ELR2020-06-30
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels✓ Link90.93CAL2021-02-10
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels✓ Link90.33Co-Teaching2018-04-18
Combating noisy labels by agreement: A joint training method with co-regularization✓ Link90.30JoCoR2020-03-05
To Smooth or Not? When Label Smoothing Meets Noisy Labels✓ Link90.29Negative-LS2021-06-08
DivideMix: Learning with Noisy Labels as Semi-supervised Learning✓ Link90.18Divide-Mix2020-02-18
Does label smoothing mitigate label noise?89.80Positive-LS2020-03-05
How does Disagreement Help Generalization against Label Corruption?✓ Link89.70Co-Teaching+2019-01-14
When Optimizing $f$-divergence is Robust with Label Noise✓ Link89.70F-div2020-11-07
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach✓ Link89.66CORES2020-10-05
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates✓ Link89.06Peer Loss2019-10-08
Are Anchor Points Really Indispensable in Label-Noise Learning?✓ Link88.33T-Revision2019-06-01
Provably End-to-end Label-Noise Learning without Anchor Points✓ Link88.30VolMinNet2021-02-04
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels✓ Link87.61GCE2018-05-20
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach✓ Link87.14Backward-T2016-09-13
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach✓ Link86.88Forward-T2016-09-13
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