label noise

Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization ICML 2021 Learning Student Networks in the Wild CVPR 2021 Learning to Purify Noisy Labels via Meta Soft Label Corrector AAAI 2021 Learning with Feature-Dependent Label Noise: A Progressive Approach ICLR 2021 Learning with Group Noise AAAI 2021 Learning with Instance-Dependent Label Noise: A Sample Sieve Approach ICLR 2021 Lower-Bounded Proper Losses for Weakly Supervised Classification ICML 2021 Me-Momentum: Extracting Hard Confident Examples From Noisily Labeled Data ICCV 2021 MoPro: Webly Supervised Learning with Momentum Prototypes ICLR 2021 Multi-level Generative Models for Partial Label Learning with Non-random Label Noise IJCAI 2021 Multi-Objective Interpolation Training for Robustness To Label Noise CVPR 2021 Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data ACL 2021 Noise as a Resource for Learning in Knowledge Distillation WACV 2021 Noisy Concurrent Training for Efficient Learning Under Label Noise WACV 2021 Optimizing Black-box Metrics with Iterative Example Weighting ICML 2021 Prototypical Representation Learning for Relation Extraction ICLR 2021 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise ICML 2021 Provably End-to-end Label-noise Learning without Anchor Points ICML 2021 Re-Labeling ImageNet: From Single to Multi-Labels, From Global to Localized Labels CVPR 2021 RIM: Reliable Influence-based Active Learning on Graphs NeurIPS 2021 RNNP: A Robust Few-Shot Learning Approach WACV 2021 Robust early-learning: Hindering the memorization of noisy labels ICLR 2021 Robust Learning under Strong Noise via SQs AISTATS 2021 Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels AAAI 2021 Searching for Robustness: Loss Learning for Noisy Classification Tasks ICCV 2021