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Combating noisy labels by agreement: A joint training method with
  co-regularization
v1v2v3 (latest)

Combating noisy labels by agreement: A joint training method with co-regularization

5 March 2020
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
    NoLa
ArXiv (abs)PDFHTML

Papers citing "Combating noisy labels by agreement: A joint training method with co-regularization"

50 / 280 papers shown
Title
Collaborating Domain-shared and Target-specific Feature Clustering for
  Cross-domain 3D Action Recognition
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition
Qinying Liu
Zilei Wang
81
9
0
20 Jul 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 Clifton
N. Robertson
90
6
0
30 Jun 2022
Compressing Features for Learning with Noisy Labels
Compressing Features for Learning with Noisy Labels
Yingyi Chen
S. Hu
Xin Shen
C. Ai
Johan A. K. Suykens
NoLa
68
14
0
27 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
67
5
0
27 Jun 2022
Protoformer: Embedding Prototypes for Transformers
Protoformer: Embedding Prototypes for Transformers
Ashkan Farhangi
Ning Sui
Nan Hua
Haiyan Bai
Arthur Huang
Zhishan Guo
ViT
77
5
0
25 Jun 2022
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing
  Long-tailed datasets
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
Hongxin Wei
Lue Tao
Renchunzi Xie
Lei Feng
Bo An
OODD
64
39
0
17 Jun 2022
Towards Robust Ranker for Text Retrieval
Towards Robust Ranker for Text Retrieval
Yucheng Zhou
Tao Shen
Xiubo Geng
Chongyang Tao
Can Xu
Guodong Long
Binxing Jiao
Daxin Jiang
OOD
82
43
0
16 Jun 2022
To Aggregate or Not? Learning with Separate Noisy Labels
To Aggregate or Not? Learning with Separate Noisy Labels
Jiaheng Wei
Zhaowei Zhu
Tianyi Luo
Ehsan Amid
Abhishek Kumar
Yang Liu
NoLa
77
40
0
14 Jun 2022
Large Loss Matters in Weakly Supervised Multi-Label Classification
Large Loss Matters in Weakly Supervised Multi-Label Classification
Youngwook Kim
Jae Myung Kim
Zeynep Akata
Jungwook Lee
NoLa
74
47
0
08 Jun 2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized
  Transition Matrix Estimation
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation
De Cheng
Tongliang Liu
Yixiong Ning
Nannan Wang
Bo Han
Gang Niu
Xinbo Gao
Masashi Sugiyama
NoLa
82
66
0
06 Jun 2022
Hyperspherical Consistency Regularization
Hyperspherical Consistency Regularization
Cheng Tan
Zhangyang Gao
Lirong Wu
Siyuan Li
Stan Z. Li
103
26
0
02 Jun 2022
Context-based Virtual Adversarial Training for Text Classification with
  Noisy Labels
Context-based Virtual Adversarial Training for Text Classification with Noisy Labels
Do-Myoung Lee
Yeachan Kim
Chang-gyun Seo
NoLa
58
2
0
29 May 2022
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data
  Augmentation
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation
Chenyang Wang
Junjun Jiang
Xiong Zhou
Xianming Liu
71
4
0
25 May 2022
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with
  Noisy Labels
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Zhuowei Wang
Dinesh Manocha
Guodong Long
Bo Han
Jing Jiang
FedML
107
19
0
20 May 2022
FedMix: Mixed Supervised Federated Learning for Medical Image
  Segmentation
FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation
Jeffry Wicaksana
Zengqiang Yan
Dong Zhang
Xijie Huang
Huimin Wu
Xin Yang
Kwang-Ting Cheng
FedML
79
52
0
04 May 2022
From Noisy Prediction to True Label: Noisy Prediction Calibration via
  Generative Model
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
Heesun Bae
Seung-Jae Shin
Byeonghu Na
Joonho Jang
Kyungwoo Song
Il-Chul Moon
NoLa
111
26
0
02 May 2022
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning
Nazmul Karim
Umar Khalid
Ashkan Esmaeili
Nazanin Rahnavard
NoLaCLL
59
17
0
21 Apr 2022
Interventional Multi-Instance Learning with Deconfounded Instance-Level
  Prediction
Interventional Multi-Instance Learning with Deconfounded Instance-Level Prediction
Tiancheng Lin
Hongteng Xu
Canqian Yang
Yi Xu
74
25
0
20 Apr 2022
Agreement or Disagreement in Noise-tolerant Mutual Learning?
Agreement or Disagreement in Noise-tolerant Mutual Learning?
Jiarun Liu
Daguang Jiang
Yukun Yang
Ruirui Li
NoLa
59
2
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 Mian
M. Shah
NoLa
89
99
0
28 Mar 2022
Multi-class Label Noise Learning via Loss Decomposition and Centroid
  Estimation
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation
Yongliang Ding
Tao Zhou
Chuang Zhang
Yijing Luo
Juan Tang
Chen Gong
NoLa
111
4
0
21 Mar 2022
Label-efficient Hybrid-supervised Learning for Medical Image
  Segmentation
Label-efficient Hybrid-supervised Learning for Medical Image Segmentation
Junwen Pan
Qi Bi
Yanzhan Yang
Pengfei Zhu
Cheng Bian
91
21
0
10 Mar 2022
On Learning Contrastive Representations for Learning with Noisy Labels
On Learning Contrastive Representations for Learning with Noisy Labels
Linya Yi
Sheng Liu
Qi She
A. McLeod
Boyu Wang
NoLa
79
41
0
03 Mar 2022
Synergistic Network Learning and Label Correction for Noise-robust Image
  Classification
Synergistic Network Learning and Label Correction for Noise-robust Image Classification
Chen Gong
K. Bin
E. Seibel
Xin Wang
Youbing Yin
Qi Song
NoLa
93
2
0
27 Feb 2022
Dropout can Simulate Exponential Number of Models for Sample Selection
  Techniques
Dropout can Simulate Exponential Number of Models for Sample Selection Techniques
RD Samsung
56
0
0
26 Feb 2022
ASSIST: Towards Label Noise-Robust Dialogue State Tracking
ASSIST: Towards Label Noise-Robust Dialogue State Tracking
Fanghua Ye
Yue Feng
Emine Yilmaz
64
22
0
26 Feb 2022
Tripartite: Tackle Noisy Labels by a More Precise Partition
Tripartite: Tackle Noisy Labels by a More Precise Partition
Xuefeng Liang
Longshan Yao
Xingyu Liu
Ying Zhou
NoLa
75
9
0
19 Feb 2022
L2B: Learning to Bootstrap Robust Models for Combating Label Noise
L2B: Learning to Bootstrap Robust Models for Combating Label Noise
Yuyin Zhou
Xianhang Li
Fengze Liu
Qingyue Wei
Xuxi Chen
Lequan Yu
Cihang Xie
M. Lungren
Lei Xing
NoLa
90
3
0
09 Feb 2022
Identifiability of Label Noise Transition Matrix
Identifiability of Label Noise Transition Matrix
Yang Liu
Hao Cheng
Kun Zhang
NoLa
101
48
0
04 Feb 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with
  Lower-Quality Features
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
Zhaowei Zhu
Jialu Wang
Yang Liu
NoLa
97
37
0
02 Feb 2022
PCL: Peer-Contrastive Learning with Diverse Augmentations for
  Unsupervised Sentence Embeddings
PCL: Peer-Contrastive Learning with Diverse Augmentations for Unsupervised Sentence Embeddings
Qiyu Wu
Chongyang Tao
Tao Shen
Can Xu
Xiubo Geng
Daxin Jiang
SSL
63
37
0
28 Jan 2022
CrossRectify: Leveraging Disagreement for Semi-supervised Object
  Detection
CrossRectify: Leveraging Disagreement for Semi-supervised Object Detection
Cheng Ma
Xingjia Pan
QiXiang Ye
Fan Tang
Weiming Dong
Changsheng Xu
103
15
0
26 Jan 2022
PiCO+: Contrastive Label Disambiguation for Robust Partial Label
  Learning
PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning
Haobo Wang
Rui Xiao
Yixuan Li
Lei Feng
Gang Niu
Gang Chen
Jiaqi Zhao
VLM
141
31
0
22 Jan 2022
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation
Renchunzi Xie
Hongxin Wei
Lei Feng
Bo An
70
11
0
16 Jan 2022
Avoiding Overfitting: A Survey on Regularization Methods for
  Convolutional Neural Networks
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks
C. F. G. Santos
João Paulo Papa
80
229
0
10 Jan 2022
Constrained Instance and Class Reweighting for Robust Learning under
  Label Noise
Constrained Instance and Class Reweighting for Robust Learning under Label Noise
Abhishek Kumar
Ehsan Amid
NoLa
61
20
0
09 Nov 2021
Learning to Rectify for Robust Learning with Noisy Labels
Learning to Rectify for Robust Learning with Noisy Labels
Haoliang Sun
Chenhui Guo
Qinglai Wei
Zhongyi Han
Yilong Yin
NoLa
169
36
0
08 Nov 2021
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern
  Estimation
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation
Jeongeun Park
Seungyoung Shin
Sangheum Hwang
Sungjoon Choi
57
5
0
02 Nov 2021
Adaptive Hierarchical Similarity Metric Learning with Noisy Labels
Adaptive Hierarchical Similarity Metric Learning with Noisy Labels
Jiexi Yan
Lei Luo
Cheng Deng
Heng-Chiao Huang
NoLa
52
19
0
29 Oct 2021
Towards a Robust Differentiable Architecture Search under Label Noise
Towards a Robust Differentiable Architecture Search under Label Noise
Christian Simon
Piotr Koniusz
L. Petersson
Yan Han
Mehrtash Harandi
NoLaAAMLOOD
41
4
0
23 Oct 2021
Learning with Noisy Labels Revisited: A Study Using Real-World Human
  Annotations
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
147
261
0
22 Oct 2021
Noisy Annotation Refinement for Object Detection
Noisy Annotation Refinement for Object Detection
Jiafeng Mao
Qing Yu
Yoko Yamakata
Kiyoharu Aizawa
NoLa
109
11
0
20 Oct 2021
Mitigating Memorization of Noisy Labels via Regularization between
  Representations
Mitigating Memorization of Noisy Labels via Regularization between Representations
Hao Cheng
Zhaowei Zhu
Xing Sun
Yang Liu
NoLa
90
28
0
18 Oct 2021
Alleviating Noisy-label Effects in Image Classification via Probability
  Transition Matrix
Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix
Ziqi Zhang
Yuexiang Li
Hongxin Wei
Kai Ma
Tao Xu
Yefeng Zheng
NoLa
73
5
0
17 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
117
42
0
14 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict
Detecting Corrupted Labels Without Training a Model to Predict
Zhaowei Zhu
Zihao Dong
Yang Liu
NoLa
208
68
0
12 Oct 2021
Improving Distantly-Supervised Named Entity Recognition with
  Self-Collaborative Denoising Learning
Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning
Xinghua Zhang
Yu Bowen
Tingwen Liu
Zhenyu Zhang
Shuaiyi Nie
Mengge Xue
Hongbo Xu
63
22
0
09 Oct 2021
Not All Negatives are Equal: Label-Aware Contrastive Loss for
  Fine-grained Text Classification
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification
Varsha Suresh
Desmond C. Ong
VLM
107
86
0
12 Sep 2021
Confidence Adaptive Regularization for Deep Learning with Noisy Labels
Confidence Adaptive Regularization for Deep Learning with Noisy Labels
Yangdi Lu
Yang Bo
Wenbo He
NoLa
69
10
0
18 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
133
127
0
05 Aug 2021
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