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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 131–140 of 249 papers

TitleStatusHype
Bootstrapping the Relationship Between Images and Their Clean and Noisy LabelsCode0
Early Stopping Against Label Noise Without Validation DataCode0
Enhanced Meta Label Correction for Coping with Label CorruptionCode0
Learning to Detect and Retrieve Objects from Unlabeled VideosCode0
Exploring Parity Challenges in Reinforcement Learning through Curriculum Learning with Noisy LabelsCode0
Exploring the Robustness of In-Context Learning with Noisy LabelsCode0
Exploring Video-Based Driver Activity Recognition under Noisy LabelsCode0
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered BeneficialCode0
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy LabelsCode0
Labeling Chaos to Learning Harmony: Federated Learning with Noisy LabelsCode0
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