label noise

Meta-Learning for Speech Emotion Recognition Considering Ambiguity of Emotion Labels Interspeech 2020 Model-agnostic Methods for Text Classification with Inherent Noise COLING 2020 OptSLA: an Optimization-Based Approach for Sequential Label Aggregation EMNLP 2020 Part-dependent Label Noise: Towards Instance-dependent Label Noise NeurIPS 2020 Partial Multi-Label Learning via Multi-Subspace Representation IJCAI 2020 Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates ICML 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Robust Deep Ordinal Regression under Label Noise ACML 2020 Self-Adaptive Training: beyond Empirical Risk Minimization NeurIPS 2020 SELF: Learning to Filter Noisy Labels with Self-Ensembling ICLR 2020 Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data AAAI 2020 Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee ICLR 2020 Structured Probabilistic End-to-End Learning from Crowds IJCAI 2020 Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction COLING 2020 Towards Accurate and Robust Domain Adaptation under Noisy Environments IJCAI 2020 Training Noise-Robust Deep Neural Networks via Meta-Learning CVPR 2020 Using PRMSE to evaluate automated scoring systems in the presence of label noise ACL 2020 Weston-Watkins Hinge Loss and Ordered Partitions NeurIPS 2020 Adversarial Label Learning AAAI 2019 A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation ALT 2019 An Effective Label Noise Model for DNN Text Classification NAACL 2019 A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels UAI 2019 Bidirectional Active Learning with Gold-Instance-Based Human Training IJCAI 2019 Classification with unknown class-conditional label noise on non-compact feature spaces COLT 2019 Combating Label Noise in Deep Learning using Abstention ICML 2019