Kavli Affiliate: Zheng Zhu | First 5 Authors: Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu | Summary: Learning with noisy labels has aroused much research interest since data annotations, especially for large-scale datasets, may be inevitably imperfect. Recent approaches resort to a semi-supervised learning problem by dividing training samples into clean and […]
Continue.. Reliable Label Correction is a Good Booster When Learning with Extremely Noisy Labels