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Provably End-to-end Label-Noise Learning without Anchor Points
v1v2v3v4 (latest)

Provably End-to-end Label-Noise Learning without Anchor Points

International Conference on Machine Learning (ICML), 2021
4 February 2021
Xuefeng Li
Tongliang Liu
Bo Han
Gang Niu
Masashi Sugiyama
    NoLa
ArXiv (abs)PDFHTML

Papers citing "Provably End-to-end Label-Noise Learning without Anchor Points"

50 / 80 papers shown
Robustness of Minimum-Volume Nonnegative Matrix Factorization under an Expanded Sufficiently Scattered Condition
Robustness of Minimum-Volume Nonnegative Matrix Factorization under an Expanded Sufficiently Scattered Condition
Giovanni Barbarino
Nicolas Gillis
Subhayan Saha
163
0
0
06 Nov 2025
Dual-granularity Sinkhorn Distillation for Enhanced Learning from Long-tailed Noisy Data
Dual-granularity Sinkhorn Distillation for Enhanced Learning from Long-tailed Noisy Data
Feng Hong
Yu Huang
Zihua Zhao
Zhihan Zhou
Jiangchao Yao
Dongsheng Li
Y. Zhang
Y. Wang
248
2
0
09 Oct 2025
Learning Robust Diffusion Models from Imprecise Supervision
Learning Robust Diffusion Models from Imprecise Supervision
Dong-Dong Wu
Jiacheng Cui
Wei Wang
Zhiqiang She
Masashi Sugiyama
DiffM
399
0
0
03 Oct 2025
Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers
Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers
Xin-Qiang Cai
Wei Wang
Feng Liu
Tongliang Liu
Gang Niu
Masashi Sugiyama
OffRLAAML
380
14
0
01 Oct 2025
Tackling the Noisy Elephant in the Room: Label Noise-robust Out-of-Distribution Detection via Loss Correction and Low-rank Decomposition
Tackling the Noisy Elephant in the Room: Label Noise-robust Out-of-Distribution Detection via Loss Correction and Low-rank Decomposition
Tarhib Al Azad
Shahana Ibrahim
OODD
295
0
0
08 Sep 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
276
0
0
08 Aug 2025
Pseudo-label Induced Subspace Representation Learning for Robust Out-of-Distribution Detection
Pseudo-label Induced Subspace Representation Learning for Robust Out-of-Distribution Detection
Tarhib Al Azad
Faizul Rakib Sayem
Shahana Ibrahim
253
0
0
05 Aug 2025
$ε$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
εεε-Softmax: Approximating One-Hot Vectors for Mitigating Label NoiseNeural Information Processing Systems (NeurIPS), 2025
Jialiang Wang
Xiong Zhou
Deming Zhai
Junjun Jiang
Xiangyang Ji
Xianming Liu
NoLa
380
5
0
04 Aug 2025
Detect and Correct: A Selective Noise Correction Method for Learning with Noisy Labels
Detect and Correct: A Selective Noise Correction Method for Learning with Noisy Labels
Yuval Grinberg
Nimrod Harel
Jacob Goldberger
Ofir Lindenbaum
NoLa
354
1
0
19 May 2025
Regretful Decisions under Label Noise
Regretful Decisions under Label NoiseInternational Conference on Learning Representations (ICLR), 2025
Sujay Nagaraj
Yang Liu
Flavio du Pin Calmon
Berk Ustun
NoLa
562
3
0
12 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
349
3
0
09 Apr 2025
Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization
Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization
Siqi Wang
Aoming Liu
Bryan A. Plummer
OOD
343
2
0
03 Apr 2025
GeoT: Geometry-guided Instance-dependent Transition Matrix for Semi-supervised Tooth Point Cloud Segmentation
GeoT: Geometry-guided Instance-dependent Transition Matrix for Semi-supervised Tooth Point Cloud SegmentationInformation Processing in Medical Imaging (IPMI), 2025
Weihao Yu
Xiaoqing Guo
Chenxin Li
Yifan Liu
Yixuan Yuan
243
2
0
21 Mar 2025
Conformal Prediction of Classifiers with Many Classes based on Noisy Labels
Conformal Prediction of Classifiers with Many Classes based on Noisy LabelsInternational Symposium on Conformal and Probabilistic Prediction with Applications (ISCPPA), 2025
Coby Penso
Jacob Goldberger
Ethan Fetaya
408
2
0
22 Jan 2025
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy LabelsIEEE Transactions on Medical Imaging (IEEE TMI), 2024
Erjian Guo
Zicheng Wang
Zhen Zhao
Luping Zhou
NoLa
439
6
0
12 Jan 2025
Learning Locally, Revising Globally: Global Reviser for Federated
  Learning with Noisy Labels
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
Yuxin Tian
Mouxing Yang
Yuhao Zhou
Jian Wang
Qing Ye
Tongliang Liu
Gang Niu
Jiancheng Lv
FedML
369
0
0
30 Nov 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
344
0
0
10 Jul 2024
From Biased Selective Labels to Pseudo-Labels: An
  Expectation-Maximization Framework for Learning from Biased Decisions
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang
Jenna Wiens
473
1
0
27 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
341
12
0
30 May 2024
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label
  Learning
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label LearningComputer Vision and Pattern Recognition (CVPR), 2024
Rui Zhao
Bin Shi
Jianfei Ruan
Tianze Pan
Bo Dong
NoLa
294
15
0
08 May 2024
A Conformal Prediction Score that is Robust to Label Noise
A Conformal Prediction Score that is Robust to Label Noise
Coby Penso
Jacob Goldberger
465
9
0
04 May 2024
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy
  Label Learning
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
Heesun Bae
Seungjae Shin
Byeonghu Na
Il-Chul Moon
NoLa
326
10
0
05 Mar 2024
Label-Noise Robust Diffusion Models
Label-Noise Robust Diffusion Models
Byeonghu Na
Yeongmin Kim
Heesun Bae
Jung Hyun Lee
Seho Kwon
Wanmo Kang
Il-Chul Moon
NoLaDiffM
387
18
0
27 Feb 2024
Checking the Sufficiently Scattered Condition using a Global Non-Convex
  Optimization Software
Checking the Sufficiently Scattered Condition using a Global Non-Convex Optimization Software
Nicolas Gillis
Robert Luce
312
3
0
08 Feb 2024
Multiclass Learning from Noisy Labels for Non-decomposable Performance
  Measures
Multiclass Learning from Noisy Labels for Non-decomposable Performance Measures
Mingyuan Zhang
Shivani Agarwal
430
3
0
01 Feb 2024
De-Confusing Pseudo-Labels in Source-Free Domain Adaptation
De-Confusing Pseudo-Labels in Source-Free Domain AdaptationEuropean Conference on Computer Vision (ECCV), 2024
I. Diamant
Amir Rosenfeld
Idan Achituve
Jacob Goldberger
Arnon Netzer
370
7
0
03 Jan 2024
Adjustable Robust Transformer for High Myopia Screening in Optical
  Coherence Tomography
Adjustable Robust Transformer for High Myopia Screening in Optical Coherence TomographyInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
Xiao Ma
Zetian Zhang
Zexuan Ji
Kun Huang
Na Su
Songtao Yuan
Qiang Chen
150
1
0
12 Dec 2023
Regroup Median Loss for Combating Label Noise
Regroup Median Loss for Combating Label Noise
Fengpeng Li
Kemou Li
Jinyu Tian
Jiantao Zhou
NoLa
297
19
0
11 Dec 2023
A Unified Framework for Connecting Noise Modeling to Boost Noise
  Detection
A Unified Framework for Connecting Noise Modeling to Boost Noise Detection
Siqi Wang
Chau Pham
Bryan A. Plummer
NoLa
299
0
0
30 Nov 2023
Clean Label Disentangling for Medical Image Segmentation with Noisy
  Labels
Clean Label Disentangling for Medical Image Segmentation with Noisy Labels
Zicheng Wang
Zhen Zhao
Erjian Guo
Luping Zhou
359
3
0
28 Nov 2023
InstanT: Semi-supervised Learning with Instance-dependent Thresholds
InstanT: Semi-supervised Learning with Instance-dependent ThresholdsNeural Information Processing Systems (NeurIPS), 2023
Muyang Li
Runze Wu
Haoyu Liu
Jun-chen Yu
Xun Yang
Bo Han
Tongliang Liu
273
22
0
29 Oct 2023
Understanding and Mitigating the Label Noise in Pre-training on
  Downstream Tasks
Understanding and Mitigating the Label Noise in Pre-training on Downstream TasksInternational Conference on Learning Representations (ICLR), 2023
Hao Chen
Yongfeng Zhang
Ankit Shah
Ran Tao
Jianguo Huang
Berfin cSimcsek
Masashi Sugiyama
Bhiksha Raj
364
47
0
29 Sep 2023
Multi-Label Noise Transition Matrix Estimation with Label Correlations:
  Theory and Algorithm
Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm
Shikun Li
Xiaobo Xia
Han Zhang
Shiming Ge
Tongliang Liu
NoLa
229
0
0
22 Sep 2023
Regularly Truncated M-estimators for Learning with Noisy Labels
Regularly Truncated M-estimators for Learning with Noisy LabelsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Xiaobo Xia
Pengqian Lu
Chen Gong
Bo Han
Jun-chen Yu
Jun Yu
Tongliang Liu
NoLa
244
19
0
02 Sep 2023
Black-box Unsupervised Domain Adaptation with Bi-directional
  Atkinson-Shiffrin Memory
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin MemoryIEEE International Conference on Computer Vision (ICCV), 2023
Jingyi Zhang
Jiaxing Huang
Xue-Qiu Jiang
Shijian Lu
345
24
0
25 Aug 2023
Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation
Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation
Fengbei Liu
Chong Wang
Yuanhong Chen
Yuyuan Liu
G. Carneiro
NoLa
484
1
0
02 Aug 2023
Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal
  Feature Affinity Learning for Robust Video Segmentation
Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video SegmentationInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
Beilei Cui
Minqing Zhang
Mengya Xu
An-Chi Wang
Wu Yuan
Hongliang Ren
NoLa
216
5
0
12 Jul 2023
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source
  Knowledge Integration
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge IntegrationEuropean Conference on Computer Vision (ECCV), 2023
Siqi Wang
Bryan A. Plummer
337
2
0
20 Jun 2023
Deep Learning From Crowdsourced Labels: Coupled Cross-entropy
  Minimization, Identifiability, and Regularization
Deep Learning From Crowdsourced Labels: Coupled Cross-entropy Minimization, Identifiability, and RegularizationInternational Conference on Learning Representations (ICLR), 2023
Shahana Ibrahim
Tri Nguyen
Xiao Fu
255
26
0
05 Jun 2023
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative
  Modeling
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative ModelingKnowledge Discovery and Data Mining (KDD), 2023
Yuchen Zhuang
Yue Yu
Lingkai Kong
Xiang Chen
Chao Zhang
NoLaSyDaAI4CE
341
19
0
30 May 2023
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric
  Regularization Approach
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization ApproachInternational Conference on Machine Learning (ICML), 2023
Tri Nguyen
Shahana Ibrahim
Xiao Fu
218
8
0
30 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for
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DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
378
5
0
13 May 2023
Latent Class-Conditional Noise Model
Latent Class-Conditional Noise ModelIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Jiangchao Yao
Bo Han
Zhihan Zhou
Ya Zhang
Ivor W. Tsang
NoLaBDL
279
12
0
19 Feb 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Modelling Approach
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Modelling Approach
Cuong C. Nguyen
Thanh-Toan Do
G. Carneiro
NoLa
477
0
0
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Learning Confident Classifiers in the Presence of Label Noise
Learning Confident Classifiers in the Presence of Label NoiseSDM (SDM), 2023
Asma Ahmed Hashmi
Aigerim Zhumabayeva
Nikita Kotelevskii
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Mohammad Yaqub
Maxim Panov
Martin Takávc
NoLa
590
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Instance-specific Label Distribution Regularization for Learning with
  Label Noise
Instance-specific Label Distribution Regularization for Learning with Label NoiseInternational Journal of Computer Vision (IJCV), 2022
Zehui Liao
Shishuai Hu
Yutong Xie
Yong-quan Xia
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228
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SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy
  Labels
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Daehwan Kim
Kwang-seok Ryoo
Hansang Cho
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291
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Distributional Reward Estimation for Effective Multi-Agent Deep
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Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022
Jifeng Hu
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Yi-Ju Chang
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280
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Tackling Instance-Dependent Label Noise with Dynamic Distribution
  Calibration
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Manyi Zhang
Yuxin Ren
Zihao Wang
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Reduction from Complementary-Label Learning to Probability Estimates
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281
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12
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