Effects of label noise on the classification of outlier observations
Fuente:
arXiv
Saved in:
| Main Authors: | de Farias, Matheus Vinícius Barreto, de Castro, Mario |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Model-agnostic information transfer and fusion for classification with label noise
by: Guojun, Zhu, et al.
Published: (2026)
by: Guojun, Zhu, et al.
Published: (2026)
Neyman-Pearson multiclass classification under label noise via empirical likelihood
by: Zhang, Qiong, et al.
Published: (2026)
by: Zhang, Qiong, et al.
Published: (2026)
Unsupervised outlier detection to improve bird audio dataset labels
by: Collins, Bruce
Published: (2025)
by: Collins, Bruce
Published: (2025)
LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions
by: Barreto, Matheus, et al.
Published: (2026)
by: Barreto, Matheus, et al.
Published: (2026)
AlleNoise: large-scale text classification benchmark dataset with real-world label noise
by: Rączkowska, Alicja, et al.
Published: (2024)
by: Rączkowska, Alicja, et al.
Published: (2024)
Imputation using training labels and classification via label imputation
by: Nguyen, Thu, et al.
Published: (2023)
by: Nguyen, Thu, et al.
Published: (2023)
Flexi-Fuzz least squares SVM for Alzheimer's diagnosis: Tackling noise, outliers, and class imbalance
by: Akhtar, Mushir, et al.
Published: (2024)
by: Akhtar, Mushir, et al.
Published: (2024)
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise
by: Cheng, Xiuyuan, et al.
Published: (2022)
by: Cheng, Xiuyuan, et al.
Published: (2022)
Exponential Lasso: robust sparse penalization under heavy-tailed noise and outliers with exponential-type loss
by: Mai, The Tien
Published: (2025)
by: Mai, The Tien
Published: (2025)
Adaptive conformal classification with noisy labels
by: Sesia, Matteo, et al.
Published: (2023)
by: Sesia, Matteo, et al.
Published: (2023)
Detecting outliers by clustering algorithms
by: Li, Qi, et al.
Published: (2024)
by: Li, Qi, et al.
Published: (2024)
Practical estimation of the optimal classification error with soft labels and calibration
by: Ushio, Ryota, et al.
Published: (2025)
by: Ushio, Ryota, et al.
Published: (2025)
Hoeffding adaptive trees for multi-label classification on data streams
by: Esteban, Aurora, et al.
Published: (2024)
by: Esteban, Aurora, et al.
Published: (2024)
Ranking hierarchical multi-label classification results with mLPRs
by: Ye, Yuting, et al.
Published: (2022)
by: Ye, Yuting, et al.
Published: (2022)
Consistent algorithms for multi-label classification with macro-at-$k$ metrics
by: Schultheis, Erik, et al.
Published: (2024)
by: Schultheis, Erik, et al.
Published: (2024)
Explainable machine learning multi-label classification of Spanish legal judgements
by: de Arriba-Pérez, Francisco, et al.
Published: (2024)
by: de Arriba-Pérez, Francisco, et al.
Published: (2024)
GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
by: Zhao, Tianqi, et al.
Published: (2024)
by: Zhao, Tianqi, et al.
Published: (2024)
Generalized test utilities for long-tail performance in extreme multi-label classification
by: Schultheis, Erik, et al.
Published: (2023)
by: Schultheis, Erik, et al.
Published: (2023)
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective
by: Li, De, et al.
Published: (2024)
by: Li, De, et al.
Published: (2024)
Applying non-negative matrix factorization with covariates to label matrix for classification
by: Satoh, Kenichi
Published: (2025)
by: Satoh, Kenichi
Published: (2025)
Conditional outlier detection for clinical alerting
by: Hauskrecht, Milos, et al.
Published: (2026)
by: Hauskrecht, Milos, et al.
Published: (2026)
Impact of white noise in artificial neural networks trained for classification: performance and noise mitigation strategies
by: Semenova, Nadezhda, et al.
Published: (2024)
by: Semenova, Nadezhda, et al.
Published: (2024)
Dimensionality-induced information loss of outliers in deep neural networks
by: Uematsu, Kazuki, et al.
Published: (2024)
by: Uematsu, Kazuki, et al.
Published: (2024)
A clean-label graph backdoor attack method in node classification task
by: Xing, Xiaogang, et al.
Published: (2023)
by: Xing, Xiaogang, et al.
Published: (2023)
No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models
by: Legast, Magali, et al.
Published: (2026)
by: Legast, Magali, et al.
Published: (2026)
Sorted Weight Sectioning for Energy-Efficient Unstructured Sparse DNNs on Compute-in-Memory Crossbars
by: Farias, Matheus, et al.
Published: (2024)
by: Farias, Matheus, et al.
Published: (2024)
Efficient Reprogramming of Memristive Crossbars for DNNs: Weight Sorting and Bit Stucking
by: Farias, Matheus, et al.
Published: (2024)
by: Farias, Matheus, et al.
Published: (2024)
Feature Explosion: a generic optimization strategy for outlier detection algorithms
by: Li, Qi
Published: (2025)
by: Li, Qi
Published: (2025)
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classification
by: Rosu, Radu-Andrei, et al.
Published: (2024)
by: Rosu, Radu-Andrei, et al.
Published: (2024)
Multivariate outlier explanations using Shapley values and Mahalanobis distances
by: Mayrhofer, Marcus, et al.
Published: (2022)
by: Mayrhofer, Marcus, et al.
Published: (2022)
A method for outlier detection based on cluster analysis and visual expert criteria
by: Lara, Juan A., et al.
Published: (2025)
by: Lara, Juan A., et al.
Published: (2025)
Exploring space efficiency in a tree-based linear model for extreme multi-label classification
by: Lin, He-Zhe, et al.
Published: (2024)
by: Lin, He-Zhe, et al.
Published: (2024)
An empirical comparison of some outlier detection methods with longitudinal data
by: D'Orazio, Marcello
Published: (2025)
by: D'Orazio, Marcello
Published: (2025)
Training neural networks with structured noise improves classification and generalization
by: Benedetti, Marco, et al.
Published: (2023)
by: Benedetti, Marco, et al.
Published: (2023)
Robust fuzzy clustering for high-dimensional multivariate time series with outlier detection
by: Ma, Ziling, et al.
Published: (2025)
by: Ma, Ziling, et al.
Published: (2025)
SSDLabeler: Realistic semi-synthetic data generation for multi-label artifact classification in EEG
by: Akama, Taketo, et al.
Published: (2025)
by: Akama, Taketo, et al.
Published: (2025)
Consistency-guided semi-supervised outlier detection in heterogeneous data using fuzzy rough sets
by: Chen, Baiyang, et al.
Published: (2025)
by: Chen, Baiyang, et al.
Published: (2025)
An inexact LPA for DC composite optimization and application to matrix completions with outliers
by: Tao, Ting, et al.
Published: (2023)
by: Tao, Ting, et al.
Published: (2023)
Sparse outlier-robust PCA for multi-source data
by: Puchhammer, Patricia, et al.
Published: (2024)
by: Puchhammer, Patricia, et al.
Published: (2024)
Rastro-DM: data mining with a trail
by: de Castro, Marcus Vinicius Borela, et al.
Published: (2024)
by: de Castro, Marcus Vinicius Borela, et al.
Published: (2024)
Similar Items
-
Model-agnostic information transfer and fusion for classification with label noise
by: Guojun, Zhu, et al.
Published: (2026) -
Neyman-Pearson multiclass classification under label noise via empirical likelihood
by: Zhang, Qiong, et al.
Published: (2026) -
Unsupervised outlier detection to improve bird audio dataset labels
by: Collins, Bruce
Published: (2025) -
LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions
by: Barreto, Matheus, et al.
Published: (2026) -
AlleNoise: large-scale text classification benchmark dataset with real-world label noise
by: Rączkowska, Alicja, et al.
Published: (2024)