:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	de Vries, Sjoerd, Thierens, Dirk
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2409.16071
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generating the Ground Truth: Synthetic Data for Soft Label and Label Noise Research
by: de Vries, Sjoerd, et al.
Published: (2023)

Learning Confident Classifiers in the Presence of Label Noise
by: Hashmi, Asma Ahmed, et al.
Published: (2023)

Soft Label PU Learning
by: Zhao, Puning, et al.
Published: (2024)

Federated Learning with Ad-hoc Adapter Insertions: The Case of Soft-Embeddings for Training Classifier-as-Retriever
by: Fofonjka, Marijan, et al.
Published: (2025)

Soft-Label Training Preserves Epistemic Uncertainty
by: Singh, Agamdeep, et al.
Published: (2025)

Confidence Calibration of Classifiers with Many Classes
by: LeCoz, Adrien, et al.
Published: (2024)

Sharing Knowledge without Sharing Data: Stitches can improve ensembles of disjointly trained models
by: Guijt, Arthur, et al.
Published: (2025)

Classifier Chain Networks for Multi-Label Classification
by: Touw, Daniel J. W., et al.
Published: (2024)

Data-Driven Estimation of the False Positive Rate of the Bayes Binary Classifier via Soft Labels
by: Jeong, Minoh, et al.
Published: (2024)

Confident Sinkhorn Allocation for Pseudo-Labeling
by: Nguyen, Vu, et al.
Published: (2022)

Least-Ambiguous Multi-Label Classifier
by: Hagos, Misgina Tsighe, et al.
Published: (2025)

Evaluating Classifier Confidence for Surface EMG Pattern Recognition
by: Furui, Akira
Published: (2023)

CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning
by: Tian, Shiyu, et al.
Published: (2023)

A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks
by: Mandal, Saptarshi, et al.
Published: (2024)

Network Inversion for Generating Confidently Classified Counterfeits
by: Suhail, Pirzada, et al.
Published: (2025)

Label Forensics: Interpreting Hard Labels in Black-Box Text Classifier
by: Du, Mengyao, et al.
Published: (2025)

UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
by: Kharbanda, Siddhant, et al.
Published: (2024)

Confidence Self-Calibration for Multi-Label Class-Incremental Learning
by: Du, Kaile, et al.
Published: (2024)

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels
by: Jeong, Hyeonsu, et al.
Published: (2024)

Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
by: Álvarez, Verónica, et al.
Published: (2025)

A Confidence-Variance Theory for Pseudo-Label Selection in Semi-Supervised Learning
by: Liu, Jinshi, et al.
Published: (2026)

COLUR: Confidence-Oriented Learning, Unlearning and Relearning with Noisy-Label Data for Model Restoration and Refinement
by: Sui, Zhihao, et al.
Published: (2025)

Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach
by: Hassouna, Mohamed, et al.
Published: (2025)

For Better or For Worse? Learning Minimum Variance Features With Label Augmentation
by: Chidambaram, Muthu, et al.
Published: (2024)

Uncertainty Calibration of Multi-Label Bird Sound Classifiers
by: Schwinger, Raphael, et al.
Published: (2025)

Model Evaluation in the Dark: Robust Classifier Metrics with Missing Labels
by: Dervovic, Danial, et al.
Published: (2025)

Leveraging Data Augmentation and Siamese Learning for Predictive Process Monitoring
by: van Straten, Sjoerd, et al.
Published: (2025)

A Confidence-based Acquisition Model for Self-supervised Active Learning and Label Correction
by: van Niekerk, Carel, et al.
Published: (2023)

Learning New Tasks from a Few Examples with Soft-Label Prototypes
by: Singh, Avyav Kumar, et al.
Published: (2022)

Training with Confidence: Catching Silent Errors in Deep Learning Training with Automated Proactive Checks
by: Jiang, Yuxuan, et al.
Published: (2025)

Chameleons do not Forget: Prompt-Based Online Continual Learning for Next Activity Prediction
by: Hassani, Marwan, et al.
Published: (2026)

Soft Dice Confidence: A Near-Optimal Confidence Estimator for Selective Prediction in Semantic Segmentation
by: Borges, Bruno Laboissiere Camargos, et al.
Published: (2024)

Probabilistic Label Spreading: Efficient and Consistent Estimation of Soft Labels with Epistemic Uncertainty on Graphs
by: Klees, Jonathan, et al.
Published: (2026)

Better Training Data Attribution via Better Inverse Hessian-Vector Products
by: Wang, Andrew, et al.
Published: (2025)

Image-based Novel Fault Detection with Deep Learning Classifiers using Hierarchical Labels
by: Sergin, Nurettin, et al.
Published: (2024)

Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers?
by: Ullah, Nasib, et al.
Published: (2024)

Classifying Long-tailed and Label-noise Data via Disentangling and Unlearning
by: Shu, Chen, et al.
Published: (2025)

Learning to Retrieve with Weakened Labels: Robust Training under Label Noise
by: Sharma, Arnab
Published: (2025)

Confidence HNC: A Network Flow Technique for Binary Classification with Noisy Labels
by: Hochbaum, Dorit, et al.
Published: (2025)

Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domains
by: Ali, Hafiz Tiomoko, et al.
Published: (2024)