Learning to Rectify for Robust Learning with Noisy Labels

8 November 2021

Papers citing "Learning to Rectify for Robust Learning with Noisy Labels"

8 / 8 papers shown

Title
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer Yingyi Chen Xiaoke Shen Yahui Liu Qinghua Tao Johan A. K. Suykens AAML ViT 19 22 0 25 Jul 2022
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 19 20 0 07 May 2021
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment F. Cordeiro Ragav Sachdeva Vasileios Belagiannis Ian Reid G. Carneiro NoLa 11 77 0 06 Mar 2021
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 92 33 0 08 Dec 2020
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models Karishma Sharma Pinar E. Donmez Enming Luo Yan Liu I. Z. Yalniz NoLa 60 32 0 15 Mar 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 303 488 0 05 Mar 2020
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 165 664 0 07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,568 0 09 Mar 2017