Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates

8 October 2019

Yang Liu

Papers citing "Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates"

48 / 48 papers shown

Title
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning Puning Yang Qizhou Wang Zhuo Huang Tongliang Liu Chengqi Zhang Bo Han MU 36 0 0 17 May 2025
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 265 0 0 24 Apr 2025
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels Yaxuan Wang Hao Cheng Jing Xiong Qingsong Wen Han Jia Ruixuan Song Li Zhang Zhaowei Zhu Yang Liu AI4TS 67 1 0 21 Jan 2025
Effective and Robust Adversarial Training against Data and Label Corruptions Pengfei Zhang Zi Huang Xin-Shun Xu Guangdong Bai 56 4 0 07 May 2024
Optimizing Feature Selection for Binary Classification with Noisy Labels: A Genetic Algorithm Approach Vandad Imani Elaheh Moradi C. Sevilla-Salcedo Vittorio Fortino Jussi Tohka NoLa 37 0 0 12 Jan 2024
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations Heewon Kim Hyun Sung Chang Kiho Cho Jaeyun Lee Bohyung Han NoLa 28 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 37 2 0 30 Dec 2023
Learning to Segment from Noisy Annotations: A Spatial Correction Approach Jiacheng Yao Yikai Zhang Songzhu Zheng Mayank Goswami Prateek Prasanna Chao Chen 43 15 0 21 Jul 2023
Validation of the Practicability of Logical Assessment Formula for Evaluations with Inaccurate Ground-Truth Labels Yongquan Yang Hong Bu 31 0 0 06 Jul 2023
ReSup: Reliable Label Noise Suppression for Facial Expression Recognition Xiang Zhang Yan Lu Huan Yan Jingyang Huang Yusheng Ji Yu Gu 35 3 0 29 May 2023
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning Jingfeng Zhang Bo Song Haohan Wang Bo Han Tongliang Liu Lei Liu Masashi Sugiyama AAML NoLa 39 14 0 28 May 2023
Unsupervised Domain-agnostic Fake News Detection using Multi-modal Weak Signals Amila Silva Ling Luo S. Karunasekera C. Leckie 26 5 0 18 May 2023
Bayes classifier cannot be learned from noisy responses with unknown noise rates Soham Bakshi Subha Maity NoLa 24 0 0 13 Apr 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 42 6 0 22 Mar 2023
Dynamics-Aware Loss for Learning with Label Noise Xiu-Chuan Li Xiaobo Xia Fei Zhu Tongliang Liu Xu-Yao Zhang Cheng-Lin Liu NoLa AI4CE 37 6 0 21 Mar 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya Zhang Ivor W. Tsang NoLa BDL 33 8 0 19 Feb 2023
Smoothly Giving up: Robustness for Simple Models Tyler Sypherd Nathan Stromberg Richard Nock Visar Berisha Lalitha Sankar 33 1 0 17 Feb 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach Cuong C. Nguyen Thanh-Toan Do G. Carneiro NoLa 42 0 0 04 Jan 2023
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels Daehwan Kim Kwang-seok Ryoo Hansang Cho Seung Wook Kim NoLa 28 3 0 20 Nov 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 31 3 0 11 Oct 2022
TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method Jiaqi Luo Zihao Wei Junkai Man Shi-qian Xu 29 8 0 28 Sep 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 39 27 0 02 Sep 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
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation De Cheng Tongliang Liu Yixiong Ning Nannan Wang Bo Han Gang Niu Xinbo Gao Masashi Sugiyama NoLa 39 65 0 06 Jun 2022
Detecting Label Errors by using Pre-Trained Language Models Derek Chong Jenny Hong Christopher D. Manning NoLa 66 21 0 25 May 2022
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection Mingtao Feng Li-Yu Daisy Liu Liangkai Zhang Hongshan Yu Yaonan Wang Ajmal Mian 27 18 0 28 Apr 2022
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Nazmul Karim Mamshad Nayeem Rizve Nazanin Rahnavard Ajmal Mian M. Shah NoLa 42 98 0 28 Mar 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Zhaowei Zhu Jialu Wang Yang Liu NoLa 38 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
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhao-Heng Yin Pichao Wang Fan Wang Xianzhe Xu Hanling Zhang Hao Li Rong Jin 41 39 0 02 Dec 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 35 19 0 09 Nov 2021
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer Yongquan Yang Fengling Li Yani Wei Jie Chen Ning Chen Mohammad H. Alobaidi Hong Bu 31 8 0 20 Oct 2021
Mitigating Memorization of Noisy Labels via Regularization between Representations Hao Cheng Zhaowei Zhu Xing Sun Yang Liu NoLa 43 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
Being Properly Improper Tyler Sypherd Richard Nock Lalitha Sankar FaML 39 10 0 18 Jun 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
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels Erik Englesson Hossein Azizpour NoLa 34 104 0 10 May 2021
Do We Really Need Gold Samples for Sample Weighting Under Label Noise? Aritra Ghosh Andrew Lan NoLa 31 9 0 19 Apr 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew Lan NoLa 21 58 0 19 Apr 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels Zhaowei Zhu Yiwen Song Yang Liu NoLa 24 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 Kankanhalli Masashi Sugiyama AAML 27 27 0 06 Feb 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 133 121 0 04 Feb 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 22 127 0 22 Dec 2020
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 24 159 0 09 Nov 2020
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 24 54 0 07 Nov 2020
Incentives for Federated Learning: a Hypothesis Elicitation Approach Yang Liu Jiaheng Wei FedML 42 21 0 21 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 24 964 0 16 Jul 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Biwei Huang Haifeng Liu Gang Niu Dacheng Tao Masashi Sugiyama NoLa 13 67 0 14 Jun 2020