Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

5 October 2020

Zhaowei Zhu

Yang Liu

Papers citing "Learning with Instance-Dependent Label Noise: A Sample Sieve Approach"

37 / 37 papers shown

Title
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data Weiran Pan Wei Wei Feida Zhu Yong Deng NoLa 159 0 0 24 Apr 2025
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 101 15 0 11 Feb 2025
Effective and Robust Adversarial Training against Data and Label Corruptions Pengfei Zhang Zi Huang Xin-Shun Xu Guangdong Bai 51 4 0 07 May 2024
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations Heewon Kim Hyun Sung Chang Kiho Cho Jaeyun Lee Bohyung Han NoLa 26 2 0 09 Jan 2024
Mitigating the Impact of False Negatives in Dense Retrieval with Contrastive Confidence Regularization Shiqi Wang Yeqin Zhang Cam-Tu Nguyen 20 2 0 30 Dec 2023
Towards Reliable Dermatology Evaluation Benchmarks Fabian Gröger Simone Lionetti Philippe Gottfrois Alvaro Gonzalez-Jimenez Matthew Groh Roxana Daneshjou Labelling Consortium Alexander A. Navarini Marc Pouly 31 5 0 13 Sep 2023
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels Chuanyan Hu Shipeng Yan Zhitong Gao Xuming He NoLa 24 4 0 20 Jun 2023
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 33 1 0 31 May 2023
Mitigating Label Noise through Data Ambiguation Julian Lienen Eyke Hüllermeier NoLa 32 6 0 23 May 2023
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations Hao Chen Ankit Shah Jindong Wang R. Tao Yidong Wang Xingxu Xie Masashi Sugiyama Rita Singh Bhiksha Raj 34 12 0 22 May 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 36 6 0 22 Mar 2023
When Source-Free Domain Adaptation Meets Learning with Noisy Labels L. Yi Gezheng Xu Pengcheng Xu Jiaqi Li Ruizhi Pu Charles Ling A. McLeod Boyu Wang 23 39 0 31 Jan 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 33 5 0 18 Jan 2023
Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification De-Chun Cheng Haichun Tai N. Wang Zhen Wang Xinbo Gao 27 3 0 30 Nov 2022
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
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 21 3 0 11 Oct 2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels Ganlong Zhao Guanbin Li Yipeng Qin Feng Liu Yizhou Yu NoLa 33 22 0 29 Jul 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
Training Subset Selection for Weak Supervision Hunter Lang Aravindan Vijayaraghavan David Sontag NoLa 16 21 0 06 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
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 24 172 0 08 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
Feature Diversity Learning with Sample Dropout for Unsupervised Domain Adaptive Person Re-identification Chunren Tang Dingyu Xue Dongyue Chen 35 2 0 25 Jan 2022
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation Jeongeun Park Seungyoung Shin Sangheum Hwang Sungjoon Choi 17 5 0 02 Nov 2021
Mitigating Memorization of Noisy Labels via Regularization between Representations Hao Cheng Zhaowei Zhu Xing Sun Yang Liu NoLa 38 28 0 18 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 149 62 0 12 Oct 2021
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations Sheng Liu Kangning Liu Weicheng Zhu Yiqiu Shen C. Fernandez‐Granda NoLa 29 104 0 07 Oct 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 32 69 0 08 Jun 2021
Learning from Noisy Labels via Dynamic Loss Thresholding Hao Yang Youzhi Jin Zi-Hua Li Deng-Bao Wang Lei Miao Xin Geng Min-Ling Zhang NoLa AI4CE 26 6 0 01 Apr 2021
Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification Fengxiang Yang Zhun Zhong Zhiming Luo Yuanzheng Cai Yaojin Lin Shaozi Li N. Sebe NoLa 27 111 0 08 Mar 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
Understanding the Interaction of Adversarial Training with Noisy Labels Jianing Zhu Jingfeng Zhang Bo Han Tongliang Liu Gang Niu Hongxia Yang Mohan S. Kankanhalli Masashi Sugiyama AAML 21 27 0 06 Feb 2021
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 24 54 0 07 Nov 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 319 498 0 05 Mar 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 31 104 0 11 Jan 2020