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Research article

First published 2025-1

LaplaceConfidence: A graph-based approach for learning with noisy labels

Mingcai Chen, Yuntao Du, Wei Tang [...]

Intelligent Data Analysis: An International Journal

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Research article

First published 2026

HEALON: Progressive hard sample attenuation for learning with noisy labels

Kaiwen Guo, Ming Ma, Xing Xu [...]

Intelligent Data Analysis: An International Journal

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Research article

First published 2026

Semi-supervised multi-indicator noise filtered optimization for fault diagnosis of high-speed train axle box bearings under noisy labels

Guo Zhihao, Zhang Kai, Liang Jiacheng [...]

Structural Health Monitoring

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Research article

First published 2026-5

A novel fault diagnosis of high-speed train axle box bearings with adaptive curriculum self-paced learning under noisy labels

Kai Zhang, Bingwen Wang, Qing Zheng [...]

Structural Health Monitoring

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Research article

First published 2025-12

Graph Data Augmentation for Graph Convolutional Networks Learning in Robust Mental Disorder Prediction with Limited and Noisy Labels

Jiacheng Pan, Yihong Dong, Daogen Jiang [...]

Journal of Computational Biology

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Research article

First published 2025-11

Bearing fault diagnosis method based on improved meta-ResNet and sample weighting under noise label

Suchao Xie, Jiacheng Wang, Yaxin Li [...]

Structural Health Monitoring

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Research article

First published 2020-1

A latent-label denoising method for relation extraction with self-directed confidence learning

Tingting Sun, Chunhong Zhang, Yang Ji [...]

Intelligent Data Analysis: An International Journal

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Research article

First published 2014-7

A new loss function for robust classification

Lei Zhao, Musa Mammadov, John Yearwood

Intelligent Data Analysis: An International Journal

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Research article

First published 2006-8

A boosting approach to remove class label noise 1

Amitava Karmaker, Stephen Kwek

International Journal of Hybrid Intelligent Systems

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Research article

First published 2022-9

Label noise detection under the noise at random model with ensemble filters

Kecia G. Moura, Ricardo B.C. Prudêncio, George D.C. Cavalcanti

Intelligent Data Analysis: An International Journal

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