2019
Unsupervised Label Noise Modeling and Loss Correction
ICML 2019oral
Despite being robust to small amounts of label noise, convolutional neural networks trained with stochastic gradient methods have been shown to easily fit random labels. When there are a mixture of correct and mislabelled targets, networks tend to fit the former before the latter. This suggests usin…