Provably End-to-end Label-Noise Learning without Anchor Points

4 February 2021

Bo Han

Papers citing "Provably End-to-end Label-Noise Learning without Anchor Points"

23 / 23 papers shown

Title
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Erjian Guo Zicheng Wang Zhen Zhao Luping Zhou NoLa 61 0 0 12 Jan 2025
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 28 4 0 13 May 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya-Qin Zhang Ivor W. Tsang NoLa BDL 33 8 0 19 Feb 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach Cuong C. Nguyen Thanh-Toan Do G. Carneiro NoLa 37 0 0 04 Jan 2023
Learning Confident Classifiers in the Presence of Label Noise Asma Ahmed Hashmi Aigerim Zhumabayeva Nikita Kotelevskii A. Agafonov Mohammad Yaqub Maxim Panov Martin Takávc NoLa 61 2 0 02 Jan 2023
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels Daehwan Kim Kwang-seok Ryoo Hansang Cho Seung Wook Kim NoLa 24 3 0 20 Nov 2022
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning Jifeng Hu Yanchao Sun Hechang Chen Sili Huang Haiyin Piao Yi-Ju Chang Lichao Sun 13 5 0 14 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 21 3 0 11 Oct 2022
Reduction from Complementary-Label Learning to Probability Estimates Weipeng Lin Hsuan-Tien Lin 30 9 0 20 Sep 2022
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling Boshen Zhang Yuxi Li Yuanpeng Tu Jinlong Peng Yabiao Wang Cunlin Wu Yanghua Xiao Cairong Zhao NoLa 38 6 0 23 Aug 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 19 6 0 30 Jun 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 27 5 0 27 Jun 2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation De-Chun Cheng Tongliang Liu Yixiong Ning Nannan Wang Bo Han Gang Niu Xinbo Gao Masashi Sugiyama NoLa 39 65 0 06 Jun 2022
Towards Robust Adaptive Object Detection under Noisy Annotations Xinyu Liu Wuyang Li Qiushi Yang Baopu Li Yixuan Yuan 17 29 0 06 Apr 2022
SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation Xiaoqing Guo Jie Liu Tongliang Liu Yiyuan Yuan 35 27 0 29 Mar 2022
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation Yongliang Ding Tao Zhou Chuang Zhang Yijing Luo Juan Tang Chen Gong NoLa 24 4 0 21 Mar 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 27 106 0 28 Feb 2022
Dropout can Simulate Exponential Number of Models for Sample Selection Techniques RD Samsung 31 0 0 26 Feb 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Zhaowei Zhu Jialu Wang Yang Liu NoLa 35 37 0 02 Feb 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Biwei Huang Tongliang Liu NoLa 53 3 0 30 Jan 2022
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 149 62 0 12 Oct 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels Zhaowei Zhu Yiwen Song Yang Liu NoLa 13 91 0 10 Feb 2021
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 28 104 0 11 Jan 2020