label noise

SemEval-2021 Task 12: Learning with Disagreements SemEval 2021 Shape Matters: Understanding the Implicit Bias of the Noise Covariance COLT 2021 Switchable K-Class Hyperplanes for Noise-Robust Representation Learning ICCV 2021 Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model AAAI 2021 Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion IJCAI 2021 Training Dynamic based data filtering may not work for NLP datasets EMNLP 2021 Understanding Instance-Level Label Noise: Disparate Impacts and Treatments ICML 2021 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data ICML 2021 When Optimizing f-Divergence is Robust with Label Noise ICLR 2021 A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery IJCAI 2020 Aggregating Crowd Wisdom with Side Information via a Clustering-based Label-aware Autoencoder IJCAI 2020 A Topological Filter for Learning with Label Noise NeurIPS 2020 AttAN: Attention Adversarial Networks for 3D Point Cloud Semantic Segmentation IJCAI 2020 Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels ICML 2020 Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020 Can gradient clipping mitigate label noise? ICLR 2020 Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization CVPR 2020 Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels JMLR 2020 Cost-Accuracy Aware Adaptive Labeling for Active Learning AAAI 2020 Coupled-View Deep Classifier Learning from Multiple Noisy Annotators AAAI 2020 Deep Discriminative CNN with Temporal Ensembling for Ambiguously-Labeled Image Classification AAAI 2020 Deep k-NN for Noisy Labels ICML 2020 Denoising Multi-Source Weak Supervision for Neural Text Classification EMNLP 2020 Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth ICLR 2020 Distilling Effective Supervision From Severe Label Noise CVPR 2020