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SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels

20 November 2022

Papers citing "SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels"

50 / 54 papers shown

Title
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 69 23 0 29 Jul 2022
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning Yidong Wang Hao Chen Qiang Heng Wenxin Hou Yue Fan ... Marios Savvides T. Shinozaki Bhiksha Raj Bernt Schiele Xing Xie 219 278 0 15 May 2022
Learning with Neighbor Consistency for Noisy Labels Ahmet Iscen Jack Valmadre Anurag Arnab Cordelia Schmid NoLa 94 76 0 04 Feb 2022
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise Mingcai Chen Hao Cheng Yuntao Du Ming Xu Wenyu Jiang Chongjun Wang NoLa 50 26 0 06 Dec 2021
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 131 260 0 22 Oct 2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 335 895 0 15 Oct 2021
Dash: Semi-Supervised Learning with Dynamic Thresholding Yi Tian Xu Lei Shang Jinxing Ye Qi Qian Yu-Feng Li Baigui Sun Hao Li Rong Jin 105 225 0 01 Sep 2021
Understanding and Improving Early Stopping for Learning with Noisy Labels Ying-Long Bai Erkun Yang Bo Han Yanhua Yang Jiatong Li Yinian Mao Gang Niu Tongliang Liu NoLa 66 221 0 30 Jun 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Zhang Zhenmin Tang NoLa 85 135 0 24 Mar 2021
Augmentation Strategies for Learning with Noisy Labels Kento Nishi Yi Ding Alex Rich Tobias Höllerer NoLa 62 118 0 03 Mar 2021
A Survey on Deep Semi-supervised Learning Xiangli Yang Zixing Song Irwin King Zenglin Xu 108 588 0 28 Feb 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 166 123 0 04 Feb 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 69 129 0 22 Dec 2020
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 101 127 0 10 Dec 2020
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting Zeke Xie Fengxiang He Shaopeng Fu Issei Sato Dacheng Tao Masashi Sugiyama 48 61 0 12 Nov 2020
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 50 55 0 07 Nov 2020
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach Hao Cheng Zhaowei Zhu Xingyu Li Yifei Gong Xing Sun Yang Liu NoLa 68 209 0 05 Oct 2020
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
Does label smoothing mitigate label noise? Michal Lukasik Srinadh Bhojanapalli A. Menon Surinder Kumar NoLa 187 351 0 05 Mar 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 358 519 0 05 Mar 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 107 1,034 0 18 Feb 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn David Berthelot Chun-Liang Li Zizhao Zhang Nicholas Carlini E. D. Cubuk Alexey Kurakin Han Zhang Colin Raffel AAML 160 3,572 0 21 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 541 42,591 0 03 Dec 2019
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring David Berthelot Nicholas Carlini E. D. Cubuk Alexey Kurakin Kihyuk Sohn Han Zhang Colin Raffel 97 684 0 21 Nov 2019
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates Yang Liu Hongyi Guo NoLa 56 241 0 08 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 253 3,502 0 30 Sep 2019
Deep Self-Learning From Noisy Labels Jiangfan Han Ping Luo Xiaogang Wang NoLa 69 282 0 06 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
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 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
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels Kun Yi Jianxin Wu NoLa 68 418 0 19 Mar 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
Learning to Learn from Noisy Labeled Data Junnan Li Yongkang Wong Qi Zhao Mohan Kankanhalli NoLa 62 334 0 13 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
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang M. Sabuncu NoLa 85 2,610 0 20 May 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
Joint Optimization Framework for Learning with Noisy Labels Daiki Tanaka Daiki Ikami T. Yamasaki Kiyoharu Aizawa NoLa 74 712 0 30 Mar 2018
Deep Learning using Rectified Linear Units (ReLU) Abien Fred Agarap 74 3,235 0 22 Mar 2018
A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels Yifan Ding Liqiang Wang Deliang Fan Boqing Gong NoLa 58 103 0 08 Feb 2018
Combining Weakly and Webly Supervised Learning for Classifying Food Images Parneet Kaur Karan Sikka Ajay Divakaran 60 22 0 23 Dec 2017
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise Kuang-Huei Lee Xiaodong He Lei Zhang Linjun Yang NoLa 76 458 0 20 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 289 9,803 0 25 Oct 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
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 151 2,738 0 13 Apr 2017
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 187 2,567 0 07 Oct 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
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 790 36,881 0 25 Aug 2016
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning Mehdi S. M. Sajjadi Mehran Javanmardi Tolga Tasdizen BDL 85 1,116 0 14 Jun 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,196 0 16 Mar 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi 381 14,263 0 23 Feb 2016