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Iterative Learning with Open-set Noisy Labels

Iterative Learning with Open-set Noisy Labels

31 March 2018
Yisen Wang
Weiyang Liu
Xingjun Ma
James Bailey
H. Zha
Le Song
Shutao Xia
    NoLa
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Papers citing "Iterative Learning with Open-set Noisy Labels"

50 / 63 papers shown
Title
When Dynamic Data Selection Meets Data Augmentation
When Dynamic Data Selection Meets Data Augmentation
Steve Yang
Peng Ye
Furao Shen
Dongzhan Zhou
26
0
0
02 May 2025
Simultaneous Automatic Picking and Manual Picking Refinement for First-Break
Simultaneous Automatic Picking and Manual Picking Refinement for First-Break
Haowen Bai
Zixiang Zhao
Jiangshe Zhang
Yukun Cui
Chunxia Zhang
Zhenbo Guo
Yongjun Wang
56
1
0
03 Feb 2025
Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair Selection
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
69
0
0
19 Jan 2025
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Erjian Guo
Zicheng Wang
Zhen Zhao
Luping Zhou
NoLa
61
0
0
12 Jan 2025
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
Jingyi Cui
Yi-Ge Zhang
Hengyu Liu
Yisen Wang
NoLa
48
0
0
03 Jan 2025
Learning with Noisy Labels: Interconnection of Two
  Expectation-Maximizations
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations
Heewon Kim
Hyun Sung Chang
Kiho Cho
Jaeyun Lee
Bohyung Han
NoLa
26
2
0
09 Jan 2024
A Survey on Open-Set Image Recognition
A Survey on Open-Set Image Recognition
Jiaying Sun
Qiulei Dong
BDL
ObjD
32
3
0
25 Dec 2023
Omnipotent Adversarial Training in the Wild
Omnipotent Adversarial Training in the Wild
Guanlin Li
Kangjie Chen
Yuan Xu
Han Qiu
Tianwei Zhang
26
0
0
14 Jul 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
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
34
9
0
18 May 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
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
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
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
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training
  Dynamics
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics
Shoaib Ahmed Siddiqui
Nitarshan Rajkumar
Tegan Maharaj
David M. Krueger
Sara Hooker
42
27
0
20 Sep 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling
Instance-Dependent Noisy Label Learning via Graphical Modelling
Arpit Garg
Cuong C. Nguyen
Rafael Felix
Thanh-Toan Do
G. Carneiro
NoLa
34
27
0
02 Sep 2022
Maximising the Utility of Validation Sets for Imbalanced Noisy-label
  Meta-learning
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning
D. Hoang
Cuong C. Nguyen
Cuong Nguyen anh Belagiannis Vasileios
G. Carneiro
25
2
0
17 Aug 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature
  Entropy State
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State
Xinshao Wang
Yang Hua
Elyor Kodirov
S. Mukherjee
David A. Clifton
N. Robertson
19
6
0
30 Jun 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy
  Labels
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels
Chuang Zhang
Li Shen
Jian Yang
Chen Gong
NoLa
27
5
0
27 Jun 2022
Gray Learning from Non-IID Data with Out-of-distribution Samples
Gray Learning from Non-IID Data with Out-of-distribution Samples
Zhilin Zhao
LongBing Cao
Changbao Wang
OOD
OODD
33
1
0
19 Jun 2022
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels
Yangdi Lu
Wenbo He
NoLa
37
39
0
02 May 2022
Few-shot Learning with Noisy Labels
Few-shot Learning with Noisy Labels
Kevin J Liang
Samrudhdhi B. Rangrej
Vladan Petrovic
Tal Hassner
NoLa
22
47
0
12 Apr 2022
On the Importance of Asymmetry for Siamese Representation Learning
On the Importance of Asymmetry for Siamese Representation Learning
Tianlin Li
Haoqi Fan
Yuandong Tian
Daisuke Kihara
Xinlei Chen
SSL
30
51
0
01 Apr 2022
SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation
SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation
Xiaoqing Guo
Jie Liu
Tongliang Liu
Yiyuan Yuan
38
27
0
29 Mar 2022
UNICON: Combating Label Noise Through Uniform Selection and Contrastive
  Learning
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning
Nazmul Karim
Mamshad Nayeem Rizve
Nazanin Rahnavard
Ajmal Saeed Mian
M. Shah
NoLa
30
98
0
28 Mar 2022
Learning with Neighbor Consistency for Noisy Labels
Learning with Neighbor Consistency for Noisy Labels
Ahmet Iscen
Jack Valmadre
Anurag Arnab
Cordelia Schmid
NoLa
41
75
0
04 Feb 2022
SSR: An Efficient and Robust Framework for Learning with Unknown Label
  Noise
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise
Chen Feng
Georgios Tzimiropoulos
Ioannis Patras
NoLa
27
18
0
22 Nov 2021
Addressing out-of-distribution label noise in webly-labelled data
Addressing out-of-distribution label noise in webly-labelled data
Paul Albert
Diego Ortego
Eric Arazo
Noel E. O'Connor
Kevin McGuinness
NoLa
16
16
0
26 Oct 2021
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
Lokesh Nagalapatti
Mahdi S. Hosseini
FedML
22
75
0
23 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
879
0
21 Oct 2021
Continual Learning on Noisy Data Streams via Self-Purified Replay
Continual Learning on Noisy Data Streams via Self-Purified Replay
C. Kim
Jinseo Jeong
Sang-chul Moon
Gunhee Kim
CLL
40
39
0
14 Oct 2021
A robust approach for deep neural networks in presence of label noise:
  relabelling and filtering instances during training
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training
A. Gómez-Ríos
Julián Luengo
Francisco Herrera
OOD
NoLa
19
0
0
08 Sep 2021
NGC: A Unified Framework for Learning with Open-World Noisy Data
NGC: A Unified Framework for Learning with Open-World Noisy Data
Zhi-Fan Wu
Tong Wei
Jianwen Jiang
Chaojie Mao
Mingqian Tang
Yu-Feng Li
11
80
0
25 Aug 2021
kNet: A Deep kNN Network To Handle Label Noise
kNet: A Deep kNN Network To Handle Label Noise
Itzik Mizrahi
S. Avidan
NoLa
21
0
0
20 Jul 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels
Self-paced Resistance Learning against Overfitting on Noisy Labels
Xiaoshuang Shi
Zhenhua Guo
Fuyong Xing
Yun Liang
Xiaofeng Zhu
NoLa
21
20
0
07 May 2021
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label
  Environment
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment
F. Cordeiro
Ragav Sachdeva
Vasileios Belagiannis
Ian Reid
G. Carneiro
NoLa
11
77
0
06 Mar 2021
DST: Data Selection and joint Training for Learning with Noisy Labels
DST: Data Selection and joint Training for Learning with Noisy Labels
Yi Wei
Xue Mei
Xin Liu
Pengxiang Xu
NoLa
27
3
0
01 Mar 2021
Understanding the Interaction of Adversarial Training with Noisy Labels
Understanding the Interaction of Adversarial Training with Noisy Labels
Jianing Zhu
Jingfeng Zhang
Bo Han
Tongliang Liu
Gang Niu
Hongxia Yang
Mohan S. Kankanhalli
Masashi Sugiyama
AAML
24
27
0
06 Feb 2021
Attentional-Biased Stochastic Gradient Descent
Attentional-Biased Stochastic Gradient Descent
Q. Qi
Yi Tian Xu
R. L. Jin
W. Yin
Tianbao Yang
ODL
26
12
0
13 Dec 2020
Beyond Class-Conditional Assumption: A Primary Attempt to Combat
  Instance-Dependent Label Noise
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
40
122
0
10 Dec 2020
A Topological Filter for Learning with Label Noise
A Topological Filter for Learning with Label Noise
Pengxiang Wu
Songzhu Zheng
Mayank Goswami
Dimitris N. Metaxas
Chao Chen
NoLa
30
112
0
09 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise
Multi-Objective Interpolation Training for Robustness to Label Noise
Diego Ortego
Eric Arazo
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
27
112
0
08 Dec 2020
Automatic Open-World Reliability Assessment
Automatic Open-World Reliability Assessment
Mohsen Jafarzadeh
T. Ahmad
A. Dhamija
Chunchun Li
Steve Cruz
Terrance E. Boult
26
11
0
11 Nov 2020
A Survey of Label-noise Representation Learning: Past, Present and
  Future
A Survey of Label-noise Representation Learning: Past, Present and Future
Bo Han
Quanming Yao
Tongliang Liu
Gang Niu
Ivor W. Tsang
James T. Kwok
Masashi Sugiyama
NoLa
24
158
0
09 Nov 2020
Active Learning for Noisy Data Streams Using Weak and Strong Labelers
Active Learning for Noisy Data Streams Using Weak and Strong Labelers
Taraneh Younesian
Dick H. J. Epema
L. Chen
17
11
0
27 Oct 2020
Training Binary Neural Networks through Learning with Noisy Supervision
Training Binary Neural Networks through Learning with Noisy Supervision
Kai Han
Yunhe Wang
Yixing Xu
Chunjing Xu
Enhua Wu
Chang Xu
MQ
15
55
0
10 Oct 2020
MoPro: Webly Supervised Learning with Momentum Prototypes
MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li
Caiming Xiong
S. Hoi
26
94
0
17 Sep 2020
Meta Soft Label Generation for Noisy Labels
Meta Soft Label Generation for Noisy Labels
G. Algan
ilkay Ulusoy
NoLa
30
38
0
11 Jul 2020
Towards Robust Pattern Recognition: A Review
Towards Robust Pattern Recognition: A Review
Xu-Yao Zhang
Cheng-Lin Liu
C. Suen
OOD
HAI
19
102
0
12 Jun 2020
Deep learning with noisy labels: exploring techniques and remedies in
  medical image analysis
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi
Haoran Dou
Simon K. Warfield
Ali Gholipour
NoLa
18
535
0
05 Dec 2019
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