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Masking: A New Perspective of Noisy Supervision

Masking: A New Perspective of Noisy Supervision

21 May 2018
Bo Han
Jiangchao Yao
Gang Niu
Mingyuan Zhou
Ivor Tsang
Ya Zhang
Masashi Sugiyama
    NoLa
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Papers citing "Masking: A New Perspective of Noisy Supervision"

50 / 57 papers shown
Title
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
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
Junru Chen
Tianyu Cao
Ninon De Mecquenem
Jiahe Li
Zhilong Chen
F. Friederici
Yang Yang
43
1
0
31 Jul 2024
Effective and Robust Adversarial Training against Data and Label
  Corruptions
Effective and Robust Adversarial Training against Data and Label Corruptions
Pengfei Zhang
Zi Huang
Xin-Shun Xu
Guangdong Bai
51
4
0
07 May 2024
Federated Learning with Extremely Noisy Clients via Negative
  Distillation
Federated Learning with Extremely Noisy Clients via Negative Distillation
Yang Lu
Lin Chen
Yonggang Zhang
Yiliang Zhang
Bo Han
Yiu-ming Cheung
Hanzi Wang
FedML
33
9
0
20 Dec 2023
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows
  from Noisy Labels
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows from Noisy Labels
Han Yang
Tianyu Wang
Xiao Hu
Chi-Wing Fu
NoLa
51
13
0
23 Aug 2023
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label
  Non-conformity in Web Images Via a New Generalized KL Divergence
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label Non-conformity in Web Images Via a New Generalized KL Divergence
Xia Huang
Kai Fong Ernest Chong
42
2
0
19 Jul 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
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
Latent Class-Conditional Noise Model
Latent Class-Conditional Noise Model
Jiangchao Yao
Bo Han
Zhihan Zhou
Ya 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
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
The 'Problem' of Human Label Variation: On Ground Truth in Data,
  Modeling and Evaluation
The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation
Barbara Plank
30
97
0
04 Nov 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution
  Calibration
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration
Manyi Zhang
Yuxin Ren
Zihao Wang
C. Yuan
24
3
0
11 Oct 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
37
27
0
02 Sep 2022
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility
  Modeling
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling
Boshen Zhang
Yuxi Li
Yuanpeng Tu
Jinlong Peng
Yabiao Wang
Cunlin Wu
Yanghua Xiao
Cairong Zhao
NoLa
38
6
0
23 Aug 2022
Learn From All: Erasing Attention Consistency for Noisy Label Facial
  Expression Recognition
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
Yuhang Zhang
Chengrui Wang
Xu Ling
Weihong Deng
43
136
0
21 Jul 2022
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets
Yingsong Huang
Bing Bai
Shengwei Zhao
Kun Bai
Fei Wang
NoLa
28
43
0
12 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 A. Clifton
N. Robertson
19
6
0
30 Jun 2022
Transductive CLIP with Class-Conditional Contrastive Learning
Transductive CLIP with Class-Conditional Contrastive Learning
Junchu Huang
Weijie Chen
Shicai Yang
Di Xie
Shiliang Pu
Yueting Zhuang
VLM
BDL
NoLa
24
6
0
13 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-Chun Cheng
Tongliang Liu
Yixiong Ning
Nannan Wang
Bo Han
Gang Niu
Xinbo Gao
Masashi Sugiyama
NoLa
39
65
0
06 Jun 2022
Robust Meta-learning with Sampling Noise and Label Noise via
  Eigen-Reptile
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile
Dong Chen
Lingfei Wu
Siliang Tang
Xiao Yun
Bo Long
Yueting Zhuang
VLM
NoLa
28
9
0
04 Jun 2022
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
A. Bhunia
Subhadeep Koley
Abdullah Faiz Ur Rahman Khilji
Aneeshan Sain
Pinaki Nath Chowdhury
Tao Xiang
Yi-Zhe Song
AAML
22
42
0
28 Mar 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Yexiong Lin
Yu Yao
Yuxuan Du
Jun Yu
Bo Han
Biwei Huang
Tongliang Liu
NoLa
53
3
0
30 Jan 2022
Learning with Proper Partial Labels
Learning with Proper Partial Labels
Zheng Wu
Jiaqi Lv
Masashi Sugiyama
26
8
0
23 Dec 2021
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise
  Mitigation in Weakly-supervised Semantic Segmentation
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation
Yi Li
Yiqun Duan
Zhanghui Kuang
Yimin Chen
Wayne Zhang
Xiaomeng Li
30
72
0
14 Dec 2021
Sample Selection for Fair and Robust Training
Sample Selection for Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
21
61
0
27 Oct 2021
Truth Discovery in Sequence Labels from Crowds
Truth Discovery in Sequence Labels from Crowds
Nasim Sabetpour
Adithya Kulkarni
Sihong Xie
Qi Li
39
16
0
09 Sep 2021
Mitigating Memorization in Sample Selection for Learning with Noisy
  Labels
Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong
Junggi Lee
Youngchul Kwak
Young-Rae Cho
Seong-Eun Kim
Woo‐Jin Song
NoLa
18
0
0
08 Jul 2021
Federated Noisy Client Learning
Federated Noisy Client Learning
Huazhu Fu
Li Li
Bo Han
Chengzhong Xu
Ling Shao
FedML
28
26
0
24 Jun 2021
Towards Understanding Deep Learning from Noisy Labels with Small-Loss
  Criterion
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Xian-Jin Gui
Wei Wang
Zhang-Hao Tian
NoLa
33
44
0
17 Jun 2021
Multi-Class Classification from Single-Class Data with Confidences
Multi-Class Classification from Single-Class Data with Confidences
Yuzhou Cao
Lei Feng
Senlin Shu
Yitian Xu
Bo An
Gang Niu
Masashi Sugiyama
16
3
0
16 Jun 2021
CCMN: A General Framework for Learning with Class-Conditional
  Multi-Label Noise
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise
Ming-Kun Xie
Sheng-Jun Huang
NoLa
24
25
0
16 May 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy
  Labels
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
Erik Englesson
Hossein Azizpour
NoLa
34
104
0
10 May 2021
Contrastive Learning Improves Model Robustness Under Label Noise
Contrastive Learning Improves Model Robustness Under Label Noise
Aritra Ghosh
Andrew S. Lan
NoLa
21
58
0
19 Apr 2021
Learning from Noisy Labels via Dynamic Loss Thresholding
Learning from Noisy Labels via Dynamic Loss Thresholding
Hao Yang
Youzhi Jin
Zi-Hua Li
Deng-Bao Wang
Lei Miao
Xin Geng
Min-Ling Zhang
NoLa
AI4CE
32
6
0
01 Apr 2021
Collaborative Label Correction via Entropy Thresholding
Collaborative Label Correction via Entropy Thresholding
Hao Wu
Jiangchao Yao
Jiajie Wang
Yinru Chen
Ya Zhang
Yanfeng Wang
NoLa
22
4
0
31 Mar 2021
Learning from Similarity-Confidence Data
Learning from Similarity-Confidence Data
Yuzhou Cao
Lei Feng
Yitian Xu
Bo An
Gang Niu
Masashi Sugiyama
27
17
0
13 Feb 2021
Self-Supervised Person Detection in 2D Range Data using a Calibrated
  Camera
Self-Supervised Person Detection in 2D Range Data using a Calibrated Camera
Dan Jia
Mats Steinweg
Alexander Hermans
Bastian Leibe
3DPC
27
11
0
16 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
Robustness of Accuracy Metric and its Inspirations in Learning with
  Noisy Labels
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
Pengfei Chen
Junjie Ye
Guangyong Chen
Jingwei Zhao
Pheng-Ann Heng
NoLa
103
34
0
08 Dec 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
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
Learning from a Complementary-label Source Domain: Theory and Algorithms
Learning from a Complementary-label Source Domain: Theory and Algorithms
Yiyang Zhang
Feng Liu
Zhen Fang
Bo Yuan
Guangquan Zhang
Jie Lu
28
70
0
04 Aug 2020
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised
  Domain Adaptation
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation
Yiyang Zhang
Feng Liu
Zhen Fang
Bo Yuan
Guangquan Zhang
Jie Lu
17
30
0
29 Jul 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise
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
13
67
0
14 Jun 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
Rethinking Importance Weighting for Deep Learning under Distribution
  Shift
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
33
134
0
08 Jun 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon
Bo Han
Gang Niu
Tongliang Liu
Masashi Sugiyama
NoLa
37
104
0
11 Jan 2020
Learning with Multiple Complementary Labels
Learning with Multiple Complementary Labels
Lei Feng
Takuo Kaneko
Bo Han
Gang Niu
Bo An
Masashi Sugiyama
20
92
0
30 Dec 2019
SELF: Learning to Filter Noisy Labels with Self-Ensembling
SELF: Learning to Filter Noisy Labels with Self-Ensembling
Philipp Kratzer
Marc Toussaint
Thi Phuong Nhung Ngo
T. Nguyen
Jim Mainprice
Thomas Brox
NoLa
33
308
0
04 Oct 2019
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