← Learning Types
Machine Learning › Learning Types ›

Label Noise

16 directly classified papers

Papers per year

Papers

Learning with Structural Labels for Learning with Noisy Labels CVPR 2024
OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels CVPR 2023
Adaptive Textual Label Noise Learning based on Pre-trained Models EMNLP 2023
Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels IJCAI 2023
Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels NIPS 2023
Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning CVPR 2022
Robustness to Label Noise Depends on the Shape of the Noise Distribution NIPS 2022
Uncertainty-Aware Learning against Label Noise on Imbalanced Datasets AAAI 2022
Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model AAAI 2021
Multi-Objective Interpolation Training for Robustness To Label Noise CVPR 2021
Instance-adaptive training with noise-robust losses against noisy labels EMNLP 2021
Label Noise in Context ACL 2020
Cost-Accuracy Aware Adaptive Labeling for Active Learning AAAI 2020
Coupled-View Deep Classifier Learning from Multiple Noisy Annotators AAAI 2020
Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels ICML 2020
Safeguarded Dynamic Label Regression for Noisy Supervision AAAI 2019