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Co-teaching: Robust Training of Deep Neural Networks with Extremely
  Noisy Labels

Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

18 April 2018
Bo Han
Quanming Yao
Xingrui Yu
Gang Niu
Miao Xu
Weihua Hu
Ivor Tsang
Masashi Sugiyama
    NoLa
ArXivPDFHTML

Papers citing "Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels"

50 / 340 papers shown
Title
Stochastic Re-weighted Gradient Descent via Distributionally Robust
  Optimization
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
Ramnath Kumar
Kushal Majmundar
Dheeraj M. Nagaraj
A. Suggala
ODL
26
6
0
15 Jun 2023
Instance-dependent Noisy-label Learning with Graphical Model Based
  Noise-rate Estimation
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation
Arpit Garg
Cuong C. Nguyen
Rafael Felix
Thanh-Toan Do
G. Carneiro
NoLa
33
1
0
31 May 2023
ReSup: Reliable Label Noise Suppression for Facial Expression
  Recognition
ReSup: Reliable Label Noise Suppression for Facial Expression Recognition
Xiang Zhang
Yan Lu
Huan Yan
Jingyang Huang
Yusheng Ji
Yu Gu
33
3
0
29 May 2023
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise
  Learning
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
32
14
0
28 May 2023
From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
Qin Liu
Fei Wang
Chaowei Xiao
Muhao Chen
AAML
37
21
0
24 May 2023
Mitigating Label Noise through Data Ambiguation
Mitigating Label Noise through Data Ambiguation
Julian Lienen
Eyke Hüllermeier
NoLa
32
6
0
23 May 2023
Imprecise Label Learning: A Unified Framework for Learning with Various
  Imprecise Label Configurations
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
Hao Chen
Ankit Shah
Jindong Wang
R. Tao
Yidong Wang
Xingxu Xie
Masashi Sugiyama
Rita Singh
Bhiksha Raj
34
12
0
22 May 2023
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in
  Natural Language Processing
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing
Tingting Wu
Xiao Ding
Minji Tang
Haotian Zhang
Bing Qin
Ting Liu
NoLa
31
9
0
18 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for
  Meta-Learning
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
28
4
0
13 May 2023
The Power of Typed Affine Decision Structures: A Case Study
The Power of Typed Affine Decision Structures: A Case Study
Gerrit Nolte
Maximilian Schlüter
Alnis Murtovi
Bernhard Steffen
AAML
17
3
0
28 Apr 2023
Eye tracking guided deep multiple instance learning with dual
  cross-attention for fundus disease detection
Eye tracking guided deep multiple instance learning with dual cross-attention for fundus disease detection
Hongyang Jiang
Jingqi Huang
Chen Tang
Xiaoqin Zhang
Mengdi Gao
Jiang-Dong Liu
29
2
0
25 Apr 2023
Improved Naive Bayes with Mislabeled Data
Improved Naive Bayes with Mislabeled Data
Qianhan Zeng
Yingqiu Zhu
Xuening Zhu
Feifei Wang
Weichen Zhao
Shuning Sun
Meng Su
Hansheng Wang
NoLa
13
2
0
13 Apr 2023
Noisy Correspondence Learning with Meta Similarity Correction
Noisy Correspondence Learning with Meta Similarity Correction
Haocheng Han
Kaiyao Miao
Qinghua Zheng
Minnan Luo
32
28
0
13 Apr 2023
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised
  Semantic Segmentation
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation
Liang Zhu
Yingyue Li
Jiemin Fang
Yan Liu
Hao Xin
Wenyu Liu
Xinggang Wang
ViT
31
28
0
03 Apr 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data
Fairness Improves Learning from Noisily Labeled Long-Tailed Data
Jiaheng Wei
Zhaowei Zhu
Gang Niu
Tongliang Liu
Sijia Liu
Masashi Sugiyama
Yang Liu
36
6
0
22 Mar 2023
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Sungnyun Kim
Sangmin Bae
Se-Young Yun
22
9
0
20 Mar 2023
Robust probabilistic inference via a constrained transport metric
Robust probabilistic inference via a constrained transport metric
Abhisek Chakraborty
A. Bhattacharya
D. Pati
33
3
0
17 Mar 2023
Learning with Noisy Labels through Learnable Weighting and Centroid
  Similarity
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity
F. Wani
Maria Sofia Bucarelli
Fabrizio Silvestri
NoLa
37
3
0
16 Mar 2023
Model Extraction Attacks on Split Federated Learning
Model Extraction Attacks on Split Federated Learning
Jingtao Li
Adnan Siraj Rakin
Xing Chen
Li Yang
Zhezhi He
Deliang Fan
C. Chakrabarti
FedML
62
5
0
13 Mar 2023
Practical Knowledge Distillation: Using DNNs to Beat DNNs
Practical Knowledge Distillation: Using DNNs to Beat DNNs
Chungman Lee
Pavlos Anastasios Apostolopulos
Igor L. Markov
FedML
22
1
0
23 Feb 2023
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
Bowen Zhao
Chen Chen
Qian-Wei Wang
Anfeng He
Shutao Xia
31
1
0
22 Feb 2023
Latent Class-Conditional Noise Model
Latent Class-Conditional Noise Model
Jiangchao Yao
Bo Han
Zhihan Zhou
Ya-Qin Zhang
Ivor W. Tsang
NoLa
BDL
33
8
0
19 Feb 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier
Learning from Noisy Labels with Decoupled Meta Label Purifier
Yuanpeng Tu
Boshen Zhang
Yuxi Li
Liang Liu
Jian Li
Yabiao Wang
Chengjie Wang
C. Zhao
NoLa
49
27
0
14 Feb 2023
When Source-Free Domain Adaptation Meets Learning with Noisy Labels
When Source-Free Domain Adaptation Meets Learning with Noisy Labels
L. Yi
Gezheng Xu
Pengcheng Xu
Jiaqi Li
Ruizhi Pu
Charles Ling
A. McLeod
Boyu Wang
23
39
0
31 Jan 2023
Bayesian Self-Supervised Contrastive Learning
Bayesian Self-Supervised Contrastive Learning
B. Liu
Bang-wei Wang
Tianrui Li
SSL
BDL
26
4
0
27 Jan 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness
Improve Noise Tolerance of Robust Loss via Noise-Awareness
Kehui Ding
Jun Shu
Deyu Meng
Zongben Xu
NoLa
33
5
0
18 Jan 2023
SemPPL: Predicting pseudo-labels for better contrastive representations
SemPPL: Predicting pseudo-labels for better contrastive representations
Matko Bovsnjak
Pierre Harvey Richemond
Nenad Tomašev
Florian Strub
Jacob Walker
Felix Hill
Lars Buesing
Razvan Pascanu
Charles Blundell
Jovana Mitrović
SSL
VLM
41
9
0
12 Jan 2023
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
Runnan Chen
Youquan Liu
Lingdong Kong
Xinge Zhu
Yuexin Ma
Yikang Li
Yuenan Hou
Yu Qiao
Wenping Wang
CLIP
3DPC
31
139
0
12 Jan 2023
Co-training with High-Confidence Pseudo Labels for Semi-supervised
  Medical Image Segmentation
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Zhiqiang Shen
Peng Cao
Hua Yang
Xiaoli Liu
Jinzhu Yang
Osmar R. Zaiane
30
38
0
11 Jan 2023
Semi-Supervised Learning with Pseudo-Negative Labels for Image
  Classification
Semi-Supervised Learning with Pseudo-Negative Labels for Image Classification
Hao Xu
Hui Xiao
Huazheng Hao
Li Dong
Xiaojie Qiu
Chengbin Peng
VLM
SSL
11
22
0
10 Jan 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial
  Mixture Approach
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach
Cuong C. Nguyen
Thanh-Toan Do
G. Carneiro
NoLa
40
0
0
04 Jan 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Yikai Wang
Yanwei Fu
Xinwei Sun
NoLa
55
8
0
02 Jan 2023
Learning Confident Classifiers in the Presence of Label Noise
Learning Confident Classifiers in the Presence of Label Noise
Asma Ahmed Hashmi
Aigerim Zhumabayeva
Nikita Kotelevskii
A. Agafonov
Mohammad Yaqub
Maxim Panov
Martin Takávc
NoLa
61
2
0
02 Jan 2023
On-the-fly Denoising for Data Augmentation in Natural Language
  Understanding
On-the-fly Denoising for Data Augmentation in Natural Language Understanding
Tianqing Fang
Wenxuan Zhou
Fangyu Liu
Hongming Zhang
Yangqiu Song
Muhao Chen
41
1
0
20 Dec 2022
Improving group robustness under noisy labels using predictive
  uncertainty
Improving group robustness under noisy labels using predictive uncertainty
Dongpin Oh
Dae Lee
Jeunghyun Byun
Bonggun Shin
UQCV
23
3
0
14 Dec 2022
Sources of Noise in Dialogue and How to Deal with Them
Sources of Noise in Dialogue and How to Deal with Them
Derek Chen
Zhou Yu
15
2
0
06 Dec 2022
On the Overlooked Structure of Stochastic Gradients
On the Overlooked Structure of Stochastic Gradients
Zeke Xie
Qian-Yuan Tang
Mingming Sun
P. Li
31
6
0
05 Dec 2022
CrossSplit: Mitigating Label Noise Memorization through Data Splitting
CrossSplit: Mitigating Label Noise Memorization through Data Splitting
Jihye Kim
A. Baratin
Yan Zhang
Simon Lacoste-Julien
NoLa
18
7
0
03 Dec 2022
Model and Data Agreement for Learning with Noisy Labels
Model and Data Agreement for Learning with Noisy Labels
Yuhang Zhang
Weihong Deng
Xingchen Cui
Yunfeng Yin
Hongzhi Shi
Dongchao Wen
NoLa
34
5
0
02 Dec 2022
FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning
FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning
Yulei Qin
Xingyu Chen
Chao Chen
Yunhang Shen
Bohan Ren
Yun Gu
Jie-jin Yang
Chunhua Shen
44
4
0
01 Dec 2022
Denoising after Entropy-based Debiasing A Robust Training Method for
  Dataset Bias with Noisy Labels
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels
Sumyeong Ahn
Se-Young Yun
NoLa
26
2
0
01 Dec 2022
On Robust Learning from Noisy Labels: A Permutation Layer Approach
On Robust Learning from Noisy Labels: A Permutation Layer Approach
Salman Alsubaihi
Mohammed Alkhrashi
Raied Aljadaany
Fahad Albalawi
Guohao Li
NoLa
23
0
0
29 Nov 2022
Combating noisy labels in object detection datasets
Combating noisy labels in object detection datasets
K. Chachula
Jakub Lyskawa
Bartlomiej Olber
Piotr Fratczak
A. Popowicz
Krystian Radlak
NoLa
26
4
0
25 Nov 2022
Learning with Silver Standard Data for Zero-shot Relation Extraction
Tianyi Wang
Jianwei Wang
Ziqian Zeng
32
2
0
25 Nov 2022
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels
Guanlin Li
Guowen Xu
Tianwei Zhang
NoLa
ISeg
21
0
0
24 Nov 2022
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration
  Method
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method
Manyi Zhang
Xuyang Zhao
Jun Yao
Chun Yuan
Weiran Huang
38
20
0
20 Nov 2022
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy
  Labels
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels
Daehwan Kim
Kwang-seok Ryoo
Hansang Cho
Seung Wook Kim
NoLa
24
3
0
20 Nov 2022
Learning from Long-Tailed Noisy Data with Sample Selection and Balanced
  Loss
Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss
Lefan Zhang
Zhang-Hao Tian
Wujun Zhou
Wei Wang
NoLa
24
2
0
20 Nov 2022
Robust Training of Graph Neural Networks via Noise Governance
Robust Training of Graph Neural Networks via Noise Governance
Siyi Qian
Haochao Ying
Renjun Hu
Jingbo Zhou
Jintai Chen
Danny Chen
Jian Wu
NoLa
33
34
0
12 Nov 2022
DC-Check: A Data-Centric AI checklist to guide the development of
  reliable machine learning systems
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems
Nabeel Seedat
F. Imrie
M. Schaar
27
12
0
09 Nov 2022
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