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Robust Loss Functions under Label Noise for Deep Neural Networks

Robust Loss Functions under Label Noise for Deep Neural Networks

27 December 2017
Aritra Ghosh
Himanshu Kumar
P. Sastry
    NoLa
    OOD
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Papers citing "Robust Loss Functions under Label Noise for Deep Neural Networks"

50 / 145 papers shown
Title
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
Neural Regression For Scale-Varying Targets
Neural Regression For Scale-Varying Targets
Adam Khakhar
Jacob Buckman
24
1
0
14 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
The Fisher-Rao Loss for Learning under Label Noise
The Fisher-Rao Loss for Learning under Label Noise
Henrique K. Miyamoto
Fábio C. C. Meneghetti
Sueli I. R. Costa
NoLa
23
5
0
28 Oct 2022
Universal hidden monotonic trend estimation with contrastive learning
Universal hidden monotonic trend estimation with contrastive learning
Edouard Pineau
S. Razakarivony
Mauricio Gonzalez
A. Schrapffer
25
0
0
18 Oct 2022
Dual Clustering Co-teaching with Consistent Sample Mining for
  Unsupervised Person Re-Identification
Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification
Zeqi Chen
Zhichao Cui
Chi Zhang
Jiahuan Zhou
Yuehu Liu
NoLa
46
17
0
07 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of
  Noisy Labels
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels
Daniel Shwartz
Uri Stern
D. Weinshall
NoLa
33
2
0
02 Oct 2022
Class-Imbalanced Complementary-Label Learning via Weighted Loss
Class-Imbalanced Complementary-Label Learning via Weighted Loss
Meng Wei
Yong Zhou
Zhongnian Li
Xinzheng Xu
21
13
0
28 Sep 2022
TRBoost: A Generic Gradient Boosting Machine based on Trust-region
  Method
TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method
Jiaqi Luo
Zihao Wei
Junkai Man
Shi-qian Xu
21
8
0
28 Sep 2022
Weakly Supervised Medical Image Segmentation With Soft Labels and Noise
  Robust Loss
Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss
B. Felfeliyan
A. Hareendranathan
G. Kuntze
S. Wichuk
Nils D. Forkert
Jacob L. Jaremko
J. Ronsky
NoLa
35
2
0
16 Sep 2022
PanorAMS: Automatic Annotation for Detecting Objects in Urban Context
PanorAMS: Automatic Annotation for Detecting Objects in Urban Context
Inske Groenen
S. Rudinac
M. Worring
18
4
0
30 Aug 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
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
Robust Object Detection With Inaccurate Bounding Boxes
Robust Object Detection With Inaccurate Bounding Boxes
Chengxin Liu
Kewei Wang
Hao Lu
Zhiguo Cao
Ziming Zhang
13
21
0
20 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-Yue Wang
NoLa
28
43
0
12 Jul 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
31
1
0
19 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
Boosting Facial Expression Recognition by A Semi-Supervised Progressive
  Teacher
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher
Jing Jiang
Weihong Deng
29
23
0
28 May 2022
Federated Learning with Noisy User Feedback
Federated Learning with Noisy User Feedback
Rahul Sharma
Anil Ramakrishna
Ansel MacLaughlin
Anna Rumshisky
Jimit Majmudar
Clement Chung
Salman Avestimehr
Rahul Gupta
FedML
21
10
0
06 May 2022
Towards Robust Adaptive Object Detection under Noisy Annotations
Towards Robust Adaptive Object Detection under Noisy Annotations
Xinyu Liu
Wuyang Li
Qiushi Yang
Baopu Li
Yixuan Yuan
17
29
0
06 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
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
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
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
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
Feature Diversity Learning with Sample Dropout for Unsupervised Domain
  Adaptive Person Re-identification
Feature Diversity Learning with Sample Dropout for Unsupervised Domain Adaptive Person Re-identification
Chunren Tang
Dingyu Xue
Dongyue Chen
38
2
0
25 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
Semantic Clustering based Deduction Learning for Image Recognition and
  Classification
Semantic Clustering based Deduction Learning for Image Recognition and Classification
Wenchi Ma
Xuemin Tu
Bo Luo
Guanghui Wang
36
29
0
25 Dec 2021
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
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
TRACER: Extreme Attention Guided Salient Object Tracing Network
TRACER: Extreme Attention Guided Salient Object Tracing Network
Min Seok Lee
Wooseok Shin
S. W. Han
23
81
0
14 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
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
24
18
0
22 Nov 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
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
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
149
62
0
12 Oct 2021
Robustness and Reliability When Training With Noisy Labels
Robustness and Reliability When Training With Noisy Labels
Amanda Olmin
Fredrik Lindsten
OOD
NoLa
16
14
0
07 Oct 2021
Label Cleaning Multiple Instance Learning: Refining Coarse Annotations
  on Single Whole-Slide Images
Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images
Zhenzhen Wang
Carla Saoud
A. Popel
Aaron W. James
Aleksander S. Popel
Jeremias Sulam
21
21
0
22 Sep 2021
Mixing between the Cross Entropy and the Expectation Loss Terms
Mixing between the Cross Entropy and the Expectation Loss Terms
Barak Battash
Lior Wolf
Tamir Hazan
UQCV
20
0
0
12 Sep 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
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
Learning with Noisy Labels via Sparse Regularization
Learning with Noisy Labels via Sparse Regularization
Xiong Zhou
Xianming Liu
Chenyang Wang
Deming Zhai
Junjun Jiang
Xiangyang Ji
NoLa
26
51
0
31 Jul 2021
Learning with Noisy Labels for Robust Point Cloud Segmentation
Learning with Noisy Labels for Robust Point Cloud Segmentation
Shuquan Ye
Dongdong Chen
Songfang Han
Jing Liao
3DPC
31
51
0
29 Jul 2021
Memorization in Deep Neural Networks: Does the Loss Function matter?
Memorization in Deep Neural Networks: Does the Loss Function matter?
Deep Patel
P. Sastry
TDI
27
8
0
21 Jul 2021
Label noise in segmentation networks : mitigation must deal with bias
Label noise in segmentation networks : mitigation must deal with bias
Eugene Vorontsov
Samuel Kadoury
NoLa
28
19
0
05 Jul 2021
Adaptive Sample Selection for Robust Learning under Label Noise
Adaptive Sample Selection for Robust Learning under Label Noise
Deep Patel
P. Sastry
OOD
NoLa
28
29
0
29 Jun 2021
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