v1v2 (latest)

Understanding and Improving Early Stopping for Learning with Noisy Labels

30 June 2021

Bo Han

Papers citing "Understanding and Improving Early Stopping for Learning with Noisy Labels"

35 / 35 papers shown

Title
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles Andrew Millard Zheng Zhao Joshua Murphy Simon Maskell UQCV BDL 118 0 0 16 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 562 0 0 24 Apr 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression C. Kim Sangwoo Moon Jihwan Moon Dongyeon Woo Gunhee Kim NoLa 172 0 0 25 Feb 2025
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 259 19 0 11 Feb 2025
Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair Selection Zhipeng Yu Qianqian Xu Yangbangyan Jiang Yingfei Sun Qingming Huang NoLa 123 0 0 19 Jan 2025
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Erjian Guo Zicheng Wang Zhen Zhao Luping Zhou NoLa 164 0 0 12 Jan 2025
Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Xinyang Huang Chuang Zhu Ruiying Ren Shengjie Liu Tiejun Huang 183 0 0 03 Jan 2025
PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Jin Li Zitong Yu Ziqiang He Zhong Wang Xiangui Kang AAML 141 0 0 15 Dec 2024
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 104 568 0 30 Jun 2020
Normalized Loss Functions for Deep Learning with Noisy Labels Xingjun Ma Hanxun Huang Yisen Wang Simone Romano S. Erfani James Bailey NoLa 73 445 0 24 Jun 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 59 67 0 14 Jun 2020
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu Xiaobo Xia Tongliang Liu Bo Han Biwei Huang Nannan Wang Haifeng Liu Gang Niu NoLa 57 53 0 14 Jun 2020
Do We Need Zero Training Loss After Achieving Zero Training Error? Takashi Ishida Ikko Yamane Tomoya Sakai Gang Niu Masashi Sugiyama AI4CE 63 137 0 20 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 107 1,034 0 18 Feb 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 123 945 0 04 Dec 2019
SELF: Learning to Filter Noisy Labels with Self-Ensembling Philipp Kratzer Marc Toussaint Thi Phuong Nhung Ngo T. Nguyen Jim Mainprice Thomas Brox NoLa 85 317 0 04 Oct 2019
Symmetric Cross Entropy for Robust Learning with Noisy Labels Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi James Bailey NoLa 96 904 0 16 Aug 2019
Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia Tongliang Liu N. Wang Bo Han Chen Gong Gang Niu Masashi Sugiyama NoLa 73 381 0 01 Jun 2019
Curriculum Loss: Robust Learning and Generalization against Label Corruption Yueming Lyu Ivor W. Tsang NoLa 108 172 0 24 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 156 3,033 0 06 May 2019
Unsupervised Data Augmentation for Consistency Training Qizhe Xie Zihang Dai Eduard H. Hovy Minh-Thang Luong Quoc V. Le 137 2,321 0 29 Apr 2019
Unsupervised Label Noise Modeling and Loss Correction Eric Arazo Sanchez Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 90 615 0 25 Apr 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 76 787 0 14 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 242 1,655 0 28 Dec 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 78 434 0 07 Jun 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 120 2,078 0 18 Apr 2018
Iterative Learning with Open-set Noisy Labels Yisen Wang Weiyang Liu Xingjun Ma James Bailey H. Zha Le Song Shutao Xia NoLa 84 328 0 31 Mar 2018
Joint Optimization Framework for Learning with Noisy Labels Daiki Tanaka Daiki Ikami T. Yamasaki Kiyoharu Aizawa NoLa 74 712 0 30 Mar 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 289 9,803 0 25 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,920 0 25 Aug 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 128 1,825 0 16 Jun 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 348 4,635 0 10 Nov 2016
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach Giorgio Patrini A. Rozza A. Menon Richard Nock Zhuang Li NoLa 115 1,458 0 13 Sep 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 350 8,174 0 13 Aug 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015