ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1911.08059
  4. Cited By
How does Early Stopping Help Generalization against Label Noise?
v1v2v3 (latest)

How does Early Stopping Help Generalization against Label Noise?

19 November 2019
Hwanjun Song
Minseok Kim
Dongmin Park
Jae-Gil Lee
    NoLa
ArXiv (abs)PDFHTML

Papers citing "How does Early Stopping Help Generalization against Label Noise?"

43 / 43 papers shown
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
311
1
0
13 Aug 2025
FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
Seunghun Yu
Jin-Hyun Ahn
Joonhyuk Kang
FedML
208
0
0
08 Apr 2025
Early Stopping Against Label Noise Without Validation Data
Early Stopping Against Label Noise Without Validation DataInternational Conference on Learning Representations (ICLR), 2025
Suqin Yuan
Lei Feng
Tongliang Liu
NoLa
633
30
0
11 Feb 2025
Source-free Semantic Regularization Learning for Semi-supervised Domain AdaptationIEEE transactions on multimedia (TMM), 2025
Xinyang Huang
Chuang Zhu
Ruiying Ren
Shengjie Liu
Tiejun Huang
465
3
0
03 Jan 2025
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding
Zilin Du
Haoxin Li
Jianfei Yu
Boyang Li
1.3K
1
0
01 Dec 2024
Learning from Different Samples: A Source-free Framework for
  Semi-supervised Domain Adaptation
Learning from Different Samples: A Source-free Framework for Semi-supervised Domain Adaptation
Xinyang Huang
Chuang Zhu
Bowen Zhang
Shanghang Zhang
230
2
0
11 Nov 2024
Tackling Noisy Labels with Network Parameter Additive Decomposition
Tackling Noisy Labels with Network Parameter Additive Decomposition
Jingyi Wang
Xiaobo Xia
Long Lan
Xinghao Wu
Jun-chen Yu
Wenjing Yang
Bo Han
Tongliang Liu
NoLa
256
16
0
20 Mar 2024
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive
  Representation Learning
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning
Xiaoyu Liu
Beitong Zhou
Cheng Cheng
235
6
0
27 Feb 2024
How does self-supervised pretraining improve robustness against noisy
  labels across various medical image classification datasets?
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?
Bidur Khanal
Binod Bhattarai
Bishesh Khanal
Cristian A. Linte
NoLa
161
1
0
15 Jan 2024
Training on Synthetic Data Beats Real Data in Multimodal Relation
  Extraction
Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction
Zilin Du
Haoxin Li
Xu Guo
Boyang Li
299
3
0
05 Dec 2023
Improving Medical Image Classification in Noisy Labels Using Only
  Self-supervised Pretraining
Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining
Bidur Khanal
Binod Bhattarai
Bishesh Khanal
Cristian A. Linte
NoLa
198
10
0
08 Aug 2023
Omnipotent Adversarial Training in the Wild
Omnipotent Adversarial Training in the Wild
Guanlin Li
Kangjie Chen
Yuan Xu
Han Qiu
Tianwei Zhang
298
0
0
14 Jul 2023
Making Binary Classification from Multiple Unlabeled Datasets Almost
  Free of Supervision
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision
Yuhao Wu
Xiaobo Xia
Jun Yu
Bo Han
Gang Niu
Masashi Sugiyama
Tongliang Liu
248
3
0
12 Jun 2023
A Curriculum View of Robust Loss Functions
A Curriculum View of Robust Loss Functions
Zebin Ou
Yue Zhang
NoLa
224
0
0
03 May 2023
Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex
  Optimization
Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization
Peiyuan Zhang
Jiaye Teng
J.N. Zhang
275
5
0
19 Mar 2023
Pushing the Accuracy-Group Robustness Frontier with Introspective
  Self-play
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play
J. Liu
Krishnamurthy Dvijotham
Jihyeon Janel Lee
Quan Yuan
Martin Strobel
Balaji Lakshminarayanan
Deepak Ramachandran
217
5
0
11 Feb 2023
Galaxy classification: a deep learning approach for classifying Sloan
  Digital Sky Survey images
Galaxy classification: a deep learning approach for classifying Sloan Digital Sky Survey imagesMonthly notices of the Royal Astronomical Society (MNRAS), 2022
Sarvesh Gharat
Y. Dandawate
46
15
0
01 Nov 2022
A Survey of Dataset Refinement for Problems in Computer Vision Datasets
A Survey of Dataset Refinement for Problems in Computer Vision DatasetsACM Computing Surveys (ACM CSUR), 2022
Zhijing Wan
Zhixiang Wang
CheukTing Chung
Zheng Wang
342
16
0
21 Oct 2022
CNTN: Cyclic Noise-tolerant Network for Gait Recognition
CNTN: Cyclic Noise-tolerant Network for Gait Recognition
Weichen Yu
Hongyuan Yu
Yan Huang
Chunshui Cao
Liang Wang
NoLa
187
3
0
13 Oct 2022
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy
Reihaneh Torkzadehmahani
Reza Nasirigerdeh
Daniel Rueckert
Georgios Kaissis
NoLa
277
7
0
11 Oct 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling
Instance-Dependent Noisy Label Learning via Graphical ModellingIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Arpit Garg
Cuong C. Nguyen
Rafael Felix
Thanh-Toan Do
G. Carneiro
NoLa
206
42
0
02 Sep 2022
A Gift from Label Smoothing: Robust Training with Adaptive Label
  Smoothing via Auxiliary Classifier under Label Noise
A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label NoiseAAAI Conference on Artificial Intelligence (AAAI), 2022
Jongwoo Ko
Bongsoo Yi
Se-Young Yun
NoLa
232
7
0
15 Jun 2022
Robust Training under Label Noise by Over-parameterization
Robust Training under Label Noise by Over-parameterizationInternational Conference on Machine Learning (ICML), 2022
Sheng Liu
Zhihui Zhu
Qing Qu
Chong You
NoLaOOD
256
138
0
28 Feb 2022
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
Wenkai Chen
Chuang Zhu
Yi Chen
Mengting Li
Tiejun Huang
NoLa
372
14
0
02 Dec 2021
Learning with Noisy Labels by Efficient Transition Matrix Estimation to
  Combat Label Miscorrection
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
Seong Min Kye
Kwanghee Choi
Joonyoung Yi
Buru Chang
NoLa
359
26
0
29 Nov 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
208
11
0
18 Aug 2021
Disparity Between Batches as a Signal for Early Stopping
Disparity Between Batches as a Signal for Early Stopping
Mahsa Forouzesh
Patrick Thiran
278
11
0
14 Jul 2021
How Does Heterogeneous Label Noise Impact Generalization in Neural Nets?
How Does Heterogeneous Label Noise Impact Generalization in Neural Nets?International Symposium on Visual Computing (ISVC), 2021
Bidur Khanal
Christopher Kanan
NoLa
158
5
0
29 Jun 2021
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction
  for Few-Shot Classification
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot ClassificationInternational Conference on Machine Learning (ICML), 2021
Dong Lee
Sae-Young Chung
178
23
0
22 Jun 2021
Influential Rank: A New Perspective of Post-training for Robust Model
  against Noisy Labels
Influential Rank: A New Perspective of Post-training for Robust Model against Noisy Labels
Seulki Park
Hwanjun Song
Daeho Um
D. Jo
Sangdoo Yun
J. Choi
NoLa
341
0
0
14 Jun 2021
Double Descent Optimization Pattern and Aliasing: Caveats of Noisy
  Labels
Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels
Florian Dubost
Erin Hong
Max Pike
Siddharth Sharma
Siyi Tang
Nandita Bhaskhar
Christopher Lee-Messer
D. Rubin
NoLa
254
2
0
03 Jun 2021
Generation and Analysis of Feature-Dependent Pseudo Noise for Training
  Deep Neural Networks
Generation and Analysis of Feature-Dependent Pseudo Noise for Training Deep Neural NetworksIEEE International Conference on Systems, Man and Cybernetics (SMC), 2021
Sree Ram Kamabattula
Kumudha Musini
Babak Namazi
G. Sankaranarayanan
V. Devarajan
NoLa
88
0
0
22 May 2021
FINE Samples for Learning with Noisy Labels
FINE Samples for Learning with Noisy LabelsNeural Information Processing Systems (NeurIPS), 2021
Taehyeon Kim
Jongwoo Ko
Sangwook Cho
J. Choi
Se-Young Yun
NoLa
301
120
0
23 Feb 2021
Deep Learning with Label Differential Privacy
Deep Learning with Label Differential PrivacyNeural Information Processing Systems (NeurIPS), 2021
Badih Ghazi
Noah Golowich
Ravi Kumar
Pasin Manurangsi
Chiyuan Zhang
336
166
0
11 Feb 2021
Understanding Instance-Level Label Noise: Disparate Impacts and
  Treatments
Understanding Instance-Level Label Noise: Disparate Impacts and TreatmentsInternational Conference on Machine Learning (ICML), 2021
Yang Liu
NoLa
139
38
0
10 Feb 2021
Learning to Combat Noisy Labels via Classification Margins
Learning to Combat Noisy Labels via Classification Margins
Jason Lin
Jelena Bradic
NoLa
199
8
0
01 Feb 2021
Identifying Training Stop Point with Noisy Labeled Data
Identifying Training Stop Point with Noisy Labeled Data
Sree Ram Kamabattula
V. Devarajan
Babak Namazi
G. Sankaranarayanan
NoLa
203
2
0
24 Dec 2020
Semi-supervised novelty detection using ensembles with regularized
  disagreement
Semi-supervised novelty detection using ensembles with regularized disagreementConference on Uncertainty in Artificial Intelligence (UAI), 2020
A. Tifrea
E. Stavarache
Fanny Yang
UQCV
258
6
0
10 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise
Multi-Objective Interpolation Training for Robustness to Label Noise
Diego Ortego
Eric Arazo
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
289
146
0
08 Dec 2020
Robust Learning by Self-Transition for Handling Noisy Labels
Robust Learning by Self-Transition for Handling Noisy Labels
Hwanjun Song
Minseok Kim
Dongmin Park
Yooju Shin
Jae-Gil Lee
NoLa
276
44
0
08 Dec 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey
Learning from Noisy Labels with Deep Neural Networks: A SurveyIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
Hwanjun Song
Minseok Kim
Dongmin Park
Yooju Shin
Jae-Gil Lee
NoLa
1.1K
1,203
0
16 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels
Early-Learning Regularization Prevents Memorization of Noisy Labels
Sheng Liu
Jonathan Niles-Weed
N. Razavian
C. Fernandez‐Granda
NoLa
458
673
0
30 Jun 2020
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive
  Batch Selection
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch SelectionInternational Conference on Information and Knowledge Management (CIKM), 2019
Hwanjun Song
Minseok Kim
Sundong Kim
Jae-Gil Lee
259
17
0
19 Nov 2019
1