Conformal Prediction of Classifiers with Many Classes based on Noisy Labels
Fuente:
arXiv
Saved in:
| Main Authors: | Penso, Coby, Goldberger, Jacob, Fetaya, Ethan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Conformal Prediction Score that is Robust to Label Noise
by: Penso, Coby, et al.
Published: (2024)
by: Penso, Coby, et al.
Published: (2024)
Privacy-Preserving Conformal Prediction Under Local Differential Privacy
by: Penso, Coby, et al.
Published: (2025)
by: Penso, Coby, et al.
Published: (2025)
Calibration of Network Confidence for Unsupervised Domain Adaptation Using Estimated Accuracy
by: Penso, Coby, et al.
Published: (2024)
by: Penso, Coby, et al.
Published: (2024)
Confidence Calibration of Classifiers with Many Classes
by: LeCoz, Adrien, et al.
Published: (2024)
by: LeCoz, Adrien, et al.
Published: (2024)
MoGU: Mixture-of-Gaussians with Uncertainty-based Gating for Time Series Forecasting
by: Aviv, Gilad, et al.
Published: (2025)
by: Aviv, Gilad, et al.
Published: (2025)
Efficient Conformal Prediction for Regression Models under Label Noise
by: Cohen, Yahav, et al.
Published: (2025)
by: Cohen, Yahav, et al.
Published: (2025)
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
by: Zong, Chen-Chen, et al.
Published: (2024)
by: Zong, Chen-Chen, et al.
Published: (2024)
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
Potential Energy based Mixture Model for Noisy Label Learning
by: Wang, Zijia, et al.
Published: (2024)
by: Wang, Zijia, et al.
Published: (2024)
High-dimensional Learning with Noisy Labels
by: Firdoussi, Aymane El, et al.
Published: (2024)
by: Firdoussi, Aymane El, et al.
Published: (2024)
Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
by: Huang, Weipeng, et al.
Published: (2025)
by: Huang, Weipeng, et al.
Published: (2025)
Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy
by: Sui, Zhihao, et al.
Published: (2025)
by: Sui, Zhihao, et al.
Published: (2025)
TMLC-Net: Transferable Meta Label Correction for Noisy Label Learning
by: Li, Mengyang
Published: (2025)
by: Li, Mengyang
Published: (2025)
Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning
by: Nguyen, Ba Hoang Anh, et al.
Published: (2026)
by: Nguyen, Ba Hoang Anh, et al.
Published: (2026)
Online Multi-Label Classification under Noisy and Changing Label Distribution
by: Zou, Yizhang, et al.
Published: (2024)
by: Zou, Yizhang, et al.
Published: (2024)
Label Noise Robustness of Conformal Prediction
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
Improved Generalization of Weight Space Networks via Augmentations
by: Shamsian, Aviv, et al.
Published: (2024)
by: Shamsian, Aviv, et al.
Published: (2024)
Detect and Correct: A Selective Noise Correction Method for Learning with Noisy Labels
by: Grinberg, Yuval, et al.
Published: (2025)
by: Grinberg, Yuval, et al.
Published: (2025)
Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning
by: Wang, Yingxu, et al.
Published: (2025)
by: Wang, Yingxu, et al.
Published: (2025)
Learning to Clean: Reinforcement Learning for Noisy Label Correction
by: Heidari, Marzi, et al.
Published: (2025)
by: Heidari, Marzi, et al.
Published: (2025)
Learning Robust Reward Machines from Noisy Labels
by: Parac, Roko, et al.
Published: (2024)
by: Parac, Roko, et al.
Published: (2024)
Embracing Biased Transition Matrices for Complementary-Label Learning with Many Classes
by: Mai, Tan-Ha, et al.
Published: (2026)
by: Mai, Tan-Ha, et al.
Published: (2026)
Image-based Novel Fault Detection with Deep Learning Classifiers using Hierarchical Labels
by: Sergin, Nurettin, et al.
Published: (2024)
by: Sergin, Nurettin, et al.
Published: (2024)
Dynamical Label Augmentation and Calibration for Noisy Electronic Health Records
by: Li, Yuhao, et al.
Published: (2025)
by: Li, Yuhao, et al.
Published: (2025)
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity
by: Wani, Farooq Ahmad, et al.
Published: (2023)
by: Wani, Farooq Ahmad, et al.
Published: (2023)
Balanced Edge Pruning for Graph Anomaly Detection with Noisy Labels
by: Wang, Zhu, et al.
Published: (2024)
by: Wang, Zhu, et al.
Published: (2024)
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
by: Sedova, Anastasiia, et al.
Published: (2023)
by: Sedova, Anastasiia, et al.
Published: (2023)
Demystifying the Optimal Fair Classifier in Multi-Class Classification
by: Zhang, Li, et al.
Published: (2026)
by: Zhang, Li, et al.
Published: (2026)
FedNoisy: Federated Noisy Label Learning Benchmark
by: Liang, Siqi, et al.
Published: (2023)
by: Liang, Siqi, et al.
Published: (2023)
Addressing Long-Tail Noisy Label Learning Problems: a Two-Stage Solution with Label Refurbishment Considering Label Rarity
by: Wu, Ying-Hsuan, et al.
Published: (2024)
by: Wu, Ying-Hsuan, et al.
Published: (2024)
Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
by: Zhang, Yiming, et al.
Published: (2025)
by: Zhang, Yiming, et al.
Published: (2025)
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments
by: Jin, Gaojie, et al.
Published: (2024)
by: Jin, Gaojie, et al.
Published: (2024)
Tackling Noisy Clients in Federated Learning with End-to-end Label Correction
by: Jiang, Xuefeng, et al.
Published: (2024)
by: Jiang, Xuefeng, et al.
Published: (2024)
Evidential Uncertainty Sets in Deep Classifiers Using Conformal Prediction
by: Karimi, Hamed, et al.
Published: (2024)
by: Karimi, Hamed, et al.
Published: (2024)
Class-based Subset Selection for Transfer Learning under Extreme Label Shift
by: Goyal, Akul, et al.
Published: (2024)
by: Goyal, Akul, et al.
Published: (2024)
Balanced Online Class-Incremental Learning via Dual Classifiers
by: Wen, Shunjie, et al.
Published: (2025)
by: Wen, Shunjie, et al.
Published: (2025)
XNB: Explainable Class-Specific NaIve-Bayes Classifier
by: Aguilar-Ruiz, Jesus S., et al.
Published: (2024)
by: Aguilar-Ruiz, Jesus S., et al.
Published: (2024)
Adversarial Attacks in Weight-Space Classifiers
by: Shor, Tamir, et al.
Published: (2025)
by: Shor, Tamir, et al.
Published: (2025)
CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance
by: Zhang, Dongyu, et al.
Published: (2024)
by: Zhang, Dongyu, et al.
Published: (2024)
Learning from Noisy Labels for Long-tailed Data via Optimal Transport
by: Li, Mengting, et al.
Published: (2024)
by: Li, Mengting, et al.
Published: (2024)
Similar Items
-
A Conformal Prediction Score that is Robust to Label Noise
by: Penso, Coby, et al.
Published: (2024) -
Privacy-Preserving Conformal Prediction Under Local Differential Privacy
by: Penso, Coby, et al.
Published: (2025) -
Calibration of Network Confidence for Unsupervised Domain Adaptation Using Estimated Accuracy
by: Penso, Coby, et al.
Published: (2024) -
Confidence Calibration of Classifiers with Many Classes
by: LeCoz, Adrien, et al.
Published: (2024) -
MoGU: Mixture-of-Gaussians with Uncertainty-based Gating for Time Series Forecasting
by: Aviv, Gilad, et al.
Published: (2025)