label noise

Online Continual Learning on a Contaminated Data Stream With Blurry Task Boundaries CVPR 2022 Part-Based Pseudo Label Refinement for Unsupervised Person Re-Identification CVPR 2022 Partially Humanizing Weak Supervision: Towards a Better Low Resource Pipeline for Spoken Language Understanding EMNLP 2022 PICA: Point-Wise Instance and Centroid Alignment Based Few-Shot Domain Adaptive Object Detection With Loose Annotations WACV 2022 PNP: Robust Learning From Noisy Labels by Probabilistic Noise Prediction CVPR 2022 Posistive-Unlabeled Learning via Optimal Transport and Margin Distribution IJCAI 2022 PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning ACL 2022 Programmable Annotation with Diversed Heuristics and Data Denoising COLING 2022 Prototype-Anchored Learning for Learning with Imperfect Annotations ICML 2022 Prototype-Representations for Training Data Filtering in Weakly-Supervised Information Extraction EMNLP 2022 Resolving Training Biases via Influence-based Data Relabeling ICLR 2022 Robust Deep Learning from Crowds with Belief Propagation AISTATS 2022 Robustness and Reliability When Training With Noisy Labels AISTATS 2022 Robustness to Label Noise Depends on the Shape of the Noise Distribution NeurIPS 2022 Robust Training under Label Noise by Over-parameterization ICML 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ICLR 2022 SelfMix: Robust Learning against Textual Label Noise with Self-Mixup Training COLING 2022 SepLL: Separating Latent Class Labels from Weak Supervision Noise EMNLP 2022 STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing EMNLP 2022 Towards a Robust Differentiable Architecture Search Under Label Noise WACV 2022 Towards Robust Adaptive Object Detection Under Noisy Annotations CVPR 2022 Transfer and Marginalize: Explaining Away Label Noise with Privileged Information ICML 2022 Trusted Loss Correction for Noisy Multi-Label Learning ACML 2022 Uncertainty-Aware Learning against Label Noise on Imbalanced Datasets AAAI 2022 UniCon: Combating Label Noise Through Uniform Selection and Contrastive Learning CVPR 2022