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  4. Cited By
Making Deep Neural Networks Robust to Label Noise: a Loss Correction
  Approach

Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

13 September 2016
Giorgio Patrini
A. Rozza
A. Menon
Richard Nock
Lizhen Qu
    NoLa
ArXivPDFHTML

Papers citing "Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach"

50 / 265 papers shown
Title
Training Subset Selection for Weak Supervision
Training Subset Selection for Weak Supervision
Hunter Lang
Aravindan Vijayaraghavan
David Sontag
NoLa
16
21
0
06 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
25
9
0
04 Jun 2022
Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A
  Study on Text Classification for African Languages
Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African Languages
D. Zhu
Michael A. Hedderich
Fangzhou Zhai
David Ifeoluwa Adelani
Dietrich Klakow
NoLa
32
0
0
03 Jun 2022
Robustness to Label Noise Depends on the Shape of the Noise Distribution
  in Feature Space
Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space
Diane Oyen
Michal Kucer
N. Hengartner
H. Singh
NoLa
OOD
33
13
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
21
2
0
29 May 2022
Bayesian Robust Graph Contrastive Learning
Bayesian Robust Graph Contrastive Learning
Yancheng Wang
Yingzhen Yang
OOD
25
1
0
27 May 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and
  Privacy Protection
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Bingzhe Wu
Jintang Li
Junchi Yu
Yatao Bian
Hengtong Zhang
...
Guangyu Sun
Peng Cui
Zibin Zheng
Zhe Liu
P. Zhao
OOD
39
25
0
20 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
Sangmook Kim
Wonyoung Shin
Soohyuk Jang
Hwanjun Song
Se-Young Yun
31
2
0
03 May 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
Is BERT Robust to Label Noise? A Study on Learning with Noisy Labels in
  Text Classification
Is BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text Classification
D. Zhu
Michael A. Hedderich
Fangzhou Zhai
David Ifeoluwa Adelani
Dietrich Klakow
NoLa
30
32
0
20 Apr 2022
SETTI: A Self-supervised Adversarial Malware Detection Architecture in
  an IoT Environment
SETTI: A Self-supervised Adversarial Malware Detection Architecture in an IoT Environment
Marjan Golmaryami
R. Taheri
Zahra Pooranian
Mohammad Shojafar
Pei Xiao
30
12
0
16 Apr 2022
ULF: Unsupervised Labeling Function Correction using Cross-Validation
  for Weak Supervision
ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision
Anastasiia Sedova
Benjamin Roth
23
0
0
14 Apr 2022
Robust Cross-Modal Representation Learning with Progressive
  Self-Distillation
Robust Cross-Modal Representation Learning with Progressive Self-Distillation
A. Andonian
Shixing Chen
Raffay Hamid
VLM
29
54
0
10 Apr 2022
Decompositional Generation Process for Instance-Dependent Partial Label
  Learning
Decompositional Generation Process for Instance-Dependent Partial Label Learning
Congyu Qiao
Ning Xu
Xin Geng
126
75
0
08 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
23
2
0
29 Mar 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 to segment fetal brain tissue from noisy annotations
Learning to segment fetal brain tissue from noisy annotations
Davood Karimi
C. Rollins
C. Velasco-Annis
Abdelhakim Ouaalam
Ali Gholipour
26
25
0
25 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels
Selective-Supervised Contrastive Learning with Noisy Labels
Shikun Li
Xiaobo Xia
Shiming Ge
Tongliang Liu
NoLa
24
172
0
08 Mar 2022
Learning from Label Proportions by Learning with Label Noise
Learning from Label Proportions by Learning with Label Noise
Jianxin Zhang
Yutong Wang
Clayton Scott
NoLa
19
24
0
04 Mar 2022
Better Supervisory Signals by Observing Learning Paths
Better Supervisory Signals by Observing Learning Paths
Yi Ren
Shangmin Guo
Danica J. Sutherland
33
21
0
04 Mar 2022
Robust Training under Label Noise by Over-parameterization
Robust Training under Label Noise by Over-parameterization
Sheng Liu
Zhihui Zhu
Qing Qu
Chong You
NoLa
OOD
27
106
0
28 Feb 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
33
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
31
0
0
26 Feb 2022
Self-Training: A Survey
Self-Training: A Survey
Massih-Reza Amini
Vasilii Feofanov
Loïc Pauletto
Lies Hadjadj
Emilie Devijver
Yury Maximov
SSL
31
102
0
24 Feb 2022
Recent Advances in Reliable Deep Graph Learning: Inherent Noise,
  Distribution Shift, and Adversarial Attack
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack
Jintang Li
Bingzhe Wu
Chengbin Hou
Guoji Fu
Yatao Bian
Liang Chen
Junzhou Huang
Zibin Zheng
OOD
AAML
32
6
0
15 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
41
3
0
09 Feb 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
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
35
37
0
02 Feb 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
Confidence May Cheat: Self-Training on Graph Neural Networks under
  Distribution Shift
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift
Hongrui Liu
Binbin Hu
Xiao Wang
Chuan Shi
Qing Cui
Jun Zhou
92
54
0
27 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
J. Zhao
VLM
49
25
0
22 Jan 2022
Model Stability with Continuous Data Updates
Model Stability with Continuous Data Updates
Huiting Liu
Avinesh P.V.S
Siddharth Patwardhan
Peter Grasch
Sachin Agarwal
24
16
0
14 Jan 2022
Robust Contrastive Learning against Noisy Views
Robust Contrastive Learning against Noisy Views
Ching-Yao Chuang
R. Devon Hjelm
Xin Wang
Vibhav Vineet
Neel Joshi
Antonio Torralba
Stefanie Jegelka
Ya-heng Song
NoLa
13
68
0
12 Jan 2022
Relieving Long-tailed Instance Segmentation via Pairwise Class Balance
Relieving Long-tailed Instance Segmentation via Pairwise Class Balance
Yin-Yin He
Peizhen Zhang
Xiu-Shen Wei
Xinming Zhang
Jian Sun
ISeg
32
24
0
08 Jan 2022
Learning with Label Noise for Image Retrieval by Selecting Interactions
Learning with Label Noise for Image Retrieval by Selecting Interactions
Sarah Ibrahimi
Arnaud Sors
Rafael Sampaio de Rezende
S. Clinchant
NoLa
VLM
24
16
0
20 Dec 2021
The perils of being unhinged: On the accuracy of classifiers minimizing
  a noise-robust convex loss
The perils of being unhinged: On the accuracy of classifiers minimizing a noise-robust convex loss
Philip M. Long
Rocco A. Servedio
17
2
0
08 Dec 2021
Hard Sample Aware Noise Robust Learning for Histopathology Image
  Classification
Hard Sample Aware Noise Robust Learning for Histopathology Image Classification
Chuang Zhu
Wenkai Chen
T. Peng
Ying Wang
M. Jin
NoLa
31
72
0
05 Dec 2021
MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels
MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels
R. Joyce
Dev Amlani
B. Hamilton
Edward Raff
24
21
0
29 Nov 2021
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
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
20
5
0
02 Nov 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
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
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with
  Noisy Labels
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels
F. Cordeiro
Vasileios Belagiannis
Ian Reid
G. Carneiro
NoLa
30
18
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
42
10
0
20 Oct 2021
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and
  Its Application to Tumour Segmentation for Breast Cancer
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer
Yongquan Yang
Fengling Li
Yani Wei
Jie Chen
Ning Chen
Mohammad H. Alobaidi
Hong Bu
26
8
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
38
28
0
18 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget
Clean or Annotate: How to Spend a Limited Data Collection Budget
Derek Chen
Zhou Yu
Samuel R. Bowman
35
13
0
15 Oct 2021
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