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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 51–60 of 249 papers

Title	Date	Tasks	Status	Hype	Score
Faster Meta Update Strategy for Noise-Robust Deep Learning	Apr 30, 2021	Deep LearningImage Classification	CodeCode Available	1	5
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels	Dec 11, 2023	DenoisingLearning with noisy labels	CodeCode Available	1	5
DAT: Training Deep Networks Robust To Label-Noise by Matching the Feature Distributions	Jun 19, 2021	Learning with noisy labelsMemorization	CodeCode Available	1	5
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights	Feb 19, 2020	Data AugmentationGeneralization Bounds	CodeCode Available	1	5
Few-shot Learning with Noisy Labels	Apr 12, 2022	Few-Shot LearningLearning with noisy labels	CodeCode Available	1	5
FedNoisy: Federated Noisy Label Learning Benchmark	Jun 20, 2023	Federated LearningLearning with noisy labels	CodeCode Available	1	5
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model	May 2, 2022	Learning with noisy labelsPrediction	CodeCode Available	1	5
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels	May 10, 2021	Image ClassificationLearning with noisy labels	CodeCode Available	1	5
Mitigating Memorization of Noisy Labels via Regularization between Representations	Oct 18, 2021	Learning with noisy labelsMemorization	CodeCode Available	1	5
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer	Jul 25, 2022	ClassificationDomain Generalization	CodeCode Available	1	5

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