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Identifying Hard Noise in Long-Tailed Sample Distribution

Identifying Hard Noise in Long-Tailed Sample Distribution

27 July 2022
Xuanyu Yi
Kaihua Tang
Xiansheng Hua
J. Lim
Hanwang Zhang
ArXivPDFHTML

Papers citing "Identifying Hard Noise in Long-Tailed Sample Distribution"

27 / 27 papers shown
Title
Class Is Invariant to Context and Vice Versa: On Learning Invariance for
  Out-Of-Distribution Generalization
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-Of-Distribution Generalization
Jiaxin Qi
Kaihua Tang
Qianru Sun
Xiansheng Hua
Hanwang Zhang
38
12
0
06 Aug 2022
Self-Supervised Learning Disentangled Group Representation as Feature
Self-Supervised Learning Disentangled Group Representation as Feature
Tan Wang
Zhongqi Yue
Jianqiang Huang
Qianru Sun
Hanwang Zhang
OOD
61
69
0
28 Oct 2021
Robust Long-Tailed Learning under Label Noise
Robust Long-Tailed Learning under Label Noise
Tong Wei
Jiang-Xin Shi
Wei-Wei Tu
Yu-Feng Li
NoLa
69
50
0
26 Aug 2021
Co-learning: Learning from Noisy Labels with Self-supervision
Co-learning: Learning from Noisy Labels with Self-supervision
Cheng Tan
Jun Xia
Lirong Wu
Stan Z. Li
NoLa
96
124
0
05 Aug 2021
Learning Debiased Representation via Disentangled Feature Augmentation
Learning Debiased Representation via Disentangled Feature Augmentation
Jungsoo Lee
Eungyeup Kim
Juyoung Lee
Jihyeon Janel Lee
Jaegul Choo
CML
48
155
0
03 Jul 2021
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Hongxin Wei
Lue Tao
Renchunzi Xie
Bo An
NoLa
63
85
0
21 Jun 2021
Boosting Co-teaching with Compression Regularization for Label Noise
Boosting Co-teaching with Compression Regularization for Label Noise
Yingyi Chen
Xin Shen
S. Hu
Johan A. K. Suykens
NoLa
71
46
0
28 Apr 2021
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts
Xudong Wang
Long Lian
Zhongqi Miao
Ziwei Liu
Stella X. Yu
105
388
0
05 Oct 2020
Long-Tailed Classification by Keeping the Good and Removing the Bad
  Momentum Causal Effect
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
Kaihua Tang
Jianqiang Huang
Hanwang Zhang
CML
98
446
0
28 Sep 2020
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Jiawei Ren
Cunjun Yu
Shunan Sheng
Xiao Ma
Haiyu Zhao
Shuai Yi
Hongsheng Li
198
570
0
21 Jul 2020
Long-tail learning via logit adjustment
Long-tail learning via logit adjustment
A. Menon
Sadeep Jayasumana
A. S. Rawat
Himanshu Jain
Andreas Veit
Sanjiv Kumar
109
707
0
14 Jul 2020
Normalized Loss Functions for Deep Learning with Noisy Labels
Normalized Loss Functions for Deep Learning with Noisy Labels
Xingjun Ma
Hanxun Huang
Yisen Wang
Simone Romano
S. Erfani
James Bailey
NoLa
65
441
0
24 Jun 2020
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition
  from a Domain Adaptation Perspective
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
Muhammad Abdullah Jamal
Matthew A. Brown
Ming-Hsuan Yang
Liqiang Wang
Boqing Gong
87
264
0
24 Mar 2020
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
NoLa
345
513
0
05 Mar 2020
Deep Representation Learning on Long-tailed Data: A Learnable Embedding
  Augmentation Perspective
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective
Jialun Liu
Yifan Sun
Chuchu Han
Zhaopeng Dou
Wenhui Li
58
206
0
25 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
Junnan Li
R. Socher
Guosheng Lin
NoLa
96
1,026
0
18 Feb 2020
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed
  Visual Recognition
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
Boyan Zhou
Quan Cui
Xiu-Shen Wei
Zhao-Min Chen
285
798
0
05 Dec 2019
Decoupling Representation and Classifier for Long-Tailed Recognition
Decoupling Representation and Classifier for Long-Tailed Recognition
Bingyi Kang
Saining Xie
Marcus Rohrbach
Zhicheng Yan
Albert Gordo
Jiashi Feng
Yannis Kalantidis
OODD
172
1,213
0
21 Oct 2019
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise
  Rates
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
Yang Liu
Hongyi Guo
NoLa
46
239
0
08 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search
  space
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
210
3,485
0
30 Sep 2019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Kaidi Cao
Colin Wei
Adrien Gaidon
Nikos Arechiga
Tengyu Ma
107
1,600
0
18 Jun 2019
Understanding and Utilizing Deep Neural Networks Trained with Noisy
  Labels
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen
B. Liao
Guangyong Chen
Shengyu Zhang
NoLa
65
386
0
13 May 2019
Unsupervised Label Noise Modeling and Loss Correction
Unsupervised Label Noise Modeling and Loss Correction
Eric Arazo Sanchez
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
74
611
0
25 Apr 2019
Large-Scale Long-Tailed Recognition in an Open World
Large-Scale Long-Tailed Recognition in an Open World
Ziwei Liu
Zhongqi Miao
Xiaohang Zhan
Jiayun Wang
Boqing Gong
Stella X. Yu
142
1,158
0
10 Apr 2019
How does Disagreement Help Generalization against Label Corruption?
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu
Bo Han
Jiangchao Yao
Gang Niu
Ivor W. Tsang
Masashi Sugiyama
NoLa
58
781
0
14 Jan 2019
Meta-Transfer Learning for Few-Shot Learning
Meta-Transfer Learning for Few-Shot Learning
Qianru Sun
Yaoyao Liu
Tat-Seng Chua
Bernt Schiele
199
1,070
0
06 Dec 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
271
9,759
0
25 Oct 2017
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