L2B: Learning to Bootstrap Robust Models for Combating Label Noise

L2B: Learning to Bootstrap Robust Models for Combating Label Noise

9 February 2022

Cihang Xie

Papers citing "L2B: Learning to Bootstrap Robust Models for Combating Label Noise"

4 / 4 papers shown

Title
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning Hanxuan Wang Na Lu Xueying Zhao Yuxuan Yan Kaipeng Ma Kwoh Chee Keong Gustavo Carneiro NoLa 54 0 0 22 Feb 2025
Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation Qingyue Wei Lequan Yu Xianhang Li Wei Shao Cihang Xie Lei Xing Yuyin Zhou 11 9 0 21 Jul 2023
Fine-Grained Classification with Noisy Labels Qi Wei Lei Feng Haoliang Sun Ren Wang Chenhui Guo Yilong Yin NoLa 103 19 0 04 Mar 2023
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 303 497 0 05 Mar 2020