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Adaptive Sample Selection for Robust Learning under Label Noise

29 June 2021

Papers citing "Adaptive Sample Selection for Robust Learning under Label Noise"

39 / 39 papers shown

Title
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew Lan NoLa 59 59 0 19 Apr 2021
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels Evgenii Zheltonozhskii Chaim Baskin A. Mendelson A. Bronstein Or Litany SSL 97 94 0 25 Mar 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels Zhaowei Zhu Yiwen Song Yang Liu NoLa 63 93 0 10 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 98 127 0 10 Dec 2020
Error-Bounded Correction of Noisy Labels Songzhu Zheng Pengxiang Wu A. Goswami Mayank Goswami Dimitris N. Metaxas Chao Chen NoLa 58 119 0 19 Nov 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 104 566 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 73 444 0 24 Jun 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 156 14,986 0 18 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 57 67 0 14 Jun 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 349 518 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
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 375 18,859 0 13 Feb 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 523 42,559 0 03 Dec 2019
Symmetric Cross Entropy for Robust Learning with Noisy Labels Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi James Bailey NoLa 96 903 0 16 Aug 2019
Curriculum Loss: Robust Learning and Generalization against Label Corruption Yueming Lyu Ivor W. Tsang NoLa 108 172 0 24 May 2019
Unsupervised Label Noise Modeling and Loss Correction Eric Arazo Sanchez Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 84 614 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
On Symmetric Losses for Learning from Corrupted Labels Nontawat Charoenphakdee Jongyeong Lee Masashi Sugiyama NoLa 79 105 0 27 Jan 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 66 787 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
Deep Bilevel Learning Simon Jenni Paolo Favaro NoLa 62 115 0 05 Sep 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 2,608 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 115 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
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 146 1,430 0 24 Mar 2018
Robust Loss Functions under Label Noise for Deep Neural Networks Aritra Ghosh Himanshu Kumar P. Sastry NoLa OOD 75 958 0 27 Dec 2017
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 111 1,456 0 14 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 282 9,797 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 125 1,823 0 16 Jun 2017
Decoupling "when to update" from "how to update" Eran Malach Shai Shalev-Shwartz NoLa 87 567 0 08 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 148 2,738 0 13 Apr 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 345 4,636 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 110 1,458 0 13 Sep 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,260 0 22 Dec 2014
Training Deep Neural Networks on Noisy Labels with Bootstrapping Scott E. Reed Honglak Lee Dragomir Anguelov Christian Szegedy D. Erhan Andrew Rabinovich NoLa 113 1,023 0 20 Dec 2014
Noise Tolerance under Risk Minimization Naresh Manwani S. M. I. P. S. Sastry NoLa 180 276 0 24 Sep 2011