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Normalized Loss Functions for Deep Learning with Noisy Labels

Normalized Loss Functions for Deep Learning with Noisy Labels

24 June 2020
Xingjun Ma
Hanxun Huang
Yisen Wang
Simone Romano
S. Erfani
James Bailey
    NoLa
ArXiv (abs)PDFHTML

Papers citing "Normalized Loss Functions for Deep Learning with Noisy Labels"

50 / 220 papers shown
Title
Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation
Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation
Lechun You
Zhonghua Wu
Weide Liu
Xulei Yang
Jun Cheng
Wei Zhou
B. Veeravalli
Guosheng Lin
3DPC
20
0
0
27 Aug 2025
Combating Noisy Labels via Dynamic Connection Masking
Combating Noisy Labels via Dynamic Connection Masking
Xinlei Zhang
Fan Liu
Chuanyi Zhang
Fan Cheng
Yuhui Zheng
NoLa
42
0
0
13 Aug 2025
Learning to Forget with Information Divergence Reweighted Objectives for Noisy Labels
Learning to Forget with Information Divergence Reweighted Objectives for Noisy Labels
Jeremiah Birrell
Reza Ebrahimi
NoLa
40
0
0
08 Aug 2025
$ε$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
εεε-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
Jialiang Wang
Xiong Zhou
Deming Zhai
Junjun Jiang
Xiangyang Ji
Xianming Liu
NoLa
46
4
0
04 Aug 2025
RoNFA: Robust Neural Field-based Approach for Few-Shot Image Classification with Noisy Labels
RoNFA: Robust Neural Field-based Approach for Few-Shot Image Classification with Noisy Labels
Nan Xiang
Lifeng Xing
Dequan Jin
NoLa
77
0
0
03 Jun 2025
Think Twice before Adaptation: Improving Adaptability of DeepFake Detection via Online Test-Time Adaptation
Think Twice before Adaptation: Improving Adaptability of DeepFake Detection via Online Test-Time Adaptation
Hong-Hanh Nguyen-Le
Van-Tuan Tran
Dinh-Thuc Nguyen
Nhien-An Le-Khac
AAMLTTA
223
0
0
24 May 2025
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images
Han Li
Hu Han
S.Kevin Zhou
123
0
0
24 May 2025
Why Can Accurate Models Be Learned from Inaccurate Annotations?
Why Can Accurate Models Be Learned from Inaccurate Annotations?
Chongjie Si
Yidan Cui
Fuchao Yang
Xiaokang Yang
Wei Shen
94
0
0
22 May 2025
Mitigating Spurious Correlations with Causal Logit Perturbation
Mitigating Spurious Correlations with Causal Logit Perturbation
Xiaoling Zhou
Wei Ye
Rui Xie
Shikun Zhang
CML
137
0
0
21 May 2025
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data
Weiran Pan
Wei Wei
Feida Zhu
Yong Deng
NoLa
740
1
0
24 Apr 2025
Robust Classification with Noisy Labels Based on Posterior Maximization
Robust Classification with Noisy Labels Based on Posterior Maximization
Nicola Novello
Andrea M. Tonello
NoLa
133
1
0
09 Apr 2025
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
Bo Yuan
Yulin Chen
Yin Zhang
Wei Jiang
NoLa
168
12
0
03 Apr 2025
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Hanxuan Wang
Na Lu
Xueying Zhao
Yuxuan Yan
Kaipeng Ma
Kwoh Chee Keong
Gustavo Carneiro
NoLa
165
1
0
22 Feb 2025
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
Jingyi Cui
Yi-Ge Zhang
Hengyu Liu
Yisen Wang
NoLa
127
2
0
03 Jan 2025
Learning Causal Transition Matrix for Instance-dependent Label Noise
Learning Causal Transition Matrix for Instance-dependent Label Noise
Jiahui Li
Tai-wei Chang
Kun Kuang
Ximing Li
Long Chen
Zhiqiang Zhang
NoLaCML
711
1
0
18 Dec 2024
Combating Semantic Contamination in Learning with Label Noise
Combating Semantic Contamination in Learning with Label Noise
Wenxiao Fan
Kan Li
NoLa
687
0
0
16 Dec 2024
Optimized Gradient Clipping for Noisy Label Learning
Optimized Gradient Clipping for Noisy Label Learning
Xichen Ye
Yifan Wu
Weizhong Zhang
Xiaoqiang Li
Yifan Chen
Cheng Jin
NoLa
255
2
0
12 Dec 2024
Robust Testing for Deep Learning using Human Label Noise
Gordon Lim
Stefan Larson
Kevin Leach
NoLa
151
0
0
29 Nov 2024
Adaptive Deviation Learning for Visual Anomaly Detection with Data
  Contamination
Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination
Anindya Sundar Das
Guansong Pang
M. Bhuyan
105
1
0
14 Nov 2024
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample
  Perspective
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
Yeonsung Jung
Jaeyun Song
J. Yang
Jin-Hwa Kim
Sung-Yub Kim
Eunho Yang
210
2
0
01 Nov 2024
Self-Relaxed Joint Training: Sample Selection for Severity Estimation
  with Ordinal Noisy Labels
Self-Relaxed Joint Training: Sample Selection for Severity Estimation with Ordinal Noisy Labels
Shumpei Takezaki
Kiyohito Tanaka
S. Uchida
NoLa
89
0
0
29 Oct 2024
Informed Deep Abstaining Classifier: Investigating noise-robust training
  for diagnostic decision support systems
Informed Deep Abstaining Classifier: Investigating noise-robust training for diagnostic decision support systems
H. Schneider
Sebastian Nowak
Aditya Parikh
Yannik C. Layer
Maike Theis
Wolfgang Block
Alois M. Sprinkart
U. Attenberger
R. Sifa
NoLa
79
0
0
28 Oct 2024
Beyond Interpretability: The Gains of Feature Monosemanticity on Model
  Robustness
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang
Yifei Wang
Jingyi Cui
Xiang Pan
Qi Lei
Stefanie Jegelka
Yisen Wang
AAML
164
2
0
27 Oct 2024
The Effects of Hallucinations in Synthetic Training Data for Relation
  Extraction
The Effects of Hallucinations in Synthetic Training Data for Relation Extraction
Steven Rogulsky
Nicholas Popovic
Michael Färber
HILM
91
3
0
10 Oct 2024
Implicit to Explicit Entropy Regularization: Benchmarking ViT
  Fine-tuning under Noisy Labels
Implicit to Explicit Entropy Regularization: Benchmarking ViT Fine-tuning under Noisy Labels
Maria Marrium
Arif Mahmood
Mohammed Bennamoun
NoLaAAML
137
0
0
05 Oct 2024
Granular-ball Representation Learning for Deep CNN on Learning with
  Label Noise
Granular-ball Representation Learning for Deep CNN on Learning with Label Noise
Dawei Dai
Hao Zhu
Shuyin Xia
Guoyin Wang
SSL
101
1
0
05 Sep 2024
Theoretical Proportion Label Perturbation for Learning from Label
  Proportions in Large Bags
Theoretical Proportion Label Perturbation for Learning from Label Proportions in Large Bags
Shunsuke Kubo
Shinnosuke Matsuo
D. Suehiro
Kazuhiro Terada
Hiroaki Ito
Akihiko Yoshizawa
Ryoma Bise
208
1
0
26 Aug 2024
An Embedding is Worth a Thousand Noisy Labels
An Embedding is Worth a Thousand Noisy Labels
Francesco Di Salvo
Sebastian Doerrich
Ines Rieger
Christian Ledig
NoLa
207
1
0
26 Aug 2024
CLIPCleaner: Cleaning Noisy Labels with CLIP
CLIPCleaner: Cleaning Noisy Labels with CLIP
Chen Feng
Georgios Tzimiropoulos
Ioannis Patras
VLM
186
8
0
19 Aug 2024
Learning with Instance-Dependent Noisy Labels by Anchor Hallucination
  and Hard Sample Label Correction
Learning with Instance-Dependent Noisy Labels by Anchor Hallucination and Hard Sample Label Correction
Po-Hsuan Huang
Chia-Ching Lin
Chih-Fan Hsu
Ming-Ching Chang
Wei-Chao Chen
NoLa
108
0
0
10 Jul 2024
NoisyAG-News: A Benchmark for Addressing Instance-Dependent Noise in
  Text Classification
NoisyAG-News: A Benchmark for Addressing Instance-Dependent Noise in Text Classification
Hongfei Huang
Tingting Liang
Xixi Sun
Zikang Jin
Yuyu Yin
NoLa
94
1
0
09 Jul 2024
Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models
Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models
Xu Han
Linghao Jin
Xuezhe Ma
Xiaofeng Liu
AAML
129
5
0
02 Jul 2024
Learning with Noisy Ground Truth: From 2D Classification to 3D
  Reconstruction
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction
Yangdi Lu
Wenbo He
3DV
100
0
0
23 Jun 2024
Mitigating Noisy Supervision Using Synthetic Samples with Soft Labels
Mitigating Noisy Supervision Using Synthetic Samples with Soft Labels
Yangdi Lu
Wenbo He
NoLa
108
1
0
22 Jun 2024
Stable Neighbor Denoising for Source-free Domain Adaptive Segmentation
Stable Neighbor Denoising for Source-free Domain Adaptive Segmentation
Dong Zhao
Shuang Wang
Qi Zang
Licheng Jiao
N. Sebe
Zhun Zhong
140
5
0
10 Jun 2024
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label
  Noise
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Zhonghao Wang
Danyu Sun
Sheng Zhou
Haobo Wang
Jiapei Fan
Longtao Huang
Jiajun Bu
NoLa
119
7
0
06 Jun 2024
Slight Corruption in Pre-training Data Makes Better Diffusion Models
Slight Corruption in Pre-training Data Makes Better Diffusion Models
Hao Chen
Yujin Han
Diganta Misra
Xiang Li
Kai Hu
Difan Zou
Masashi Sugiyama
Yongfeng Zhang
Bhiksha Raj
DiffM
154
8
0
30 May 2024
A Theoretical Understanding of Self-Correction through In-context
  Alignment
A Theoretical Understanding of Self-Correction through In-context Alignment
Yifei Wang
Yuyang Wu
Zeming Wei
Stefanie Jegelka
Yisen Wang
LRM
146
38
0
28 May 2024
On the Noise Robustness of In-Context Learning for Text Generation
On the Noise Robustness of In-Context Learning for Text Generation
Hongfu Gao
Feipeng Zhang
Wenyu Jiang
Jun Shu
Feng Zheng
Jianguo Huang
165
6
0
27 May 2024
Jump-teaching: Ultra Efficient and Robust Learning with Noisy Label
Jump-teaching: Ultra Efficient and Robust Learning with Noisy Label
Kangye Ji
Fei Cheng
Zeqing Wang
Bohu Huang
NoLa
126
0
0
27 May 2024
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
Ju-Seung Byun
Andrew Perrault
84
1
0
27 May 2024
Can We Treat Noisy Labels as Accurate?
Can We Treat Noisy Labels as Accurate?
Yuxiang Zheng
Zhongyi Han
Yilong Yin
Xin Gao
Tongliang Liu
84
1
0
21 May 2024
Boosting Single Positive Multi-label Classification with Generalized
  Robust Loss
Boosting Single Positive Multi-label Classification with Generalized Robust Loss
Yanxi Chen
Chunxiao Li
Xinyang Dai
Jinhuan Li
Weiyu Sun
Yiming Wang
Renyuan Zhang
Tinghe Zhang
Bo Wang
95
5
0
06 May 2024
Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi
  Divergence
Robust Semi-supervised Learning via fff-Divergence and ααα-Rényi Divergence
Gholamali Aminian
Amirhossien Bagheri
Mahyar JafariNodeh
Radmehr Karimian
Mohammad Hossein Yassaee
77
2
0
01 May 2024
Boosting Model Resilience via Implicit Adversarial Data Augmentation
Boosting Model Resilience via Implicit Adversarial Data Augmentation
Xiaoling Zhou
Wei Ye
Zhemg Lee
Rui Xie
Shi-Bo Zhang
136
4
0
25 Apr 2024
Uncertainty-guided Open-Set Source-Free Unsupervised Domain Adaptation
  with Target-private Class Segregation
Uncertainty-guided Open-Set Source-Free Unsupervised Domain Adaptation with Target-private Class Segregation
Mattia Litrico
Davide Talon
Sebastiano Battiato
Alessio Del Bue
M. Giuffrida
Pietro Morerio
UQCV
101
0
0
16 Apr 2024
Application of Deep Learning Methods to Processing of Noisy Medical
  Video Data
Application of Deep Learning Methods to Processing of Noisy Medical Video Data
Danil Afonchikov
E. Kornaeva
Irina Makovik
Alexey Kornaev
78
0
0
16 Apr 2024
Contrastive-Based Deep Embeddings for Label Noise-Resilient
  Histopathology Image Classification
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification
Lucas Dedieu
Nicolas Nerrienet
A. Nivaggioli
Clara Simmat
Marceau Clavel
Arnaud Gauthier
Stéphane Sockeel
Rémy Peyret
NoLa
99
2
0
11 Apr 2024
Coordinated Sparse Recovery of Label Noise
Coordinated Sparse Recovery of Label Noise
Yukun Yang
Naihao Wang
Haixin Yang
Ruirui Li
NoLa
127
0
0
07 Apr 2024
Noisy Label Processing for Classification: A Survey
Noisy Label Processing for Classification: A Survey
Mengting Li
Chuang Zhu
NoLa
126
2
0
05 Apr 2024
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