:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Aguilar-Ruiz, Jesus S.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2411.01973
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robustness quantification: a new method for assessing the reliability of the predictions of a classifier
by: Detavernier, Adrián, et al.
Published: (2025)

Robustness and uncertainty: two complementary aspects of the reliability of the predictions of a classifier
by: Detavernier, Adrián, et al.
Published: (2025)

On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks
by: Pernot, Pascal
Published: (2024)

A comprehensive review of classifier probability calibration metrics
by: Lane, Richard Oliver
Published: (2025)

PolyGraph Discrepancy: a classifier-based metric for graph generation
by: Krimmel, Markus, et al.
Published: (2025)

Class-specific feature selection for classification explainability
by: Aguilar-Ruiz, Jesus S.
Published: (2024)

Computationally lightweight classifiers with frequentist bounds on predictions
by: Murali, Shreeram, et al.
Published: (2026)

Distilling the Unknown to Unveil Certainty
by: Zhao, Zhilin, et al.
Published: (2023)

Calibrating Expressions of Certainty
by: Wang, Peiqi, et al.
Published: (2024)

Irredundant $k$-Fold Cross-Validation
by: Aguilar-Ruiz, Jesus S.
Published: (2025)

Enhancing reliability in prediction intervals using point forecasters: Heteroscedastic Quantile Regression and Width-Adaptive Conformal Inference
by: Sebastián, Carlos, et al.
Published: (2024)

A novel reliability attack of Physical Unclonable Functions
by: Li, Gaoxiang, et al.
Published: (2024)

Concentration Bounds for Optimized Certainty Equivalent Risk Estimation
by: Ghosh, Ayon, et al.
Published: (2024)

Filtering instances and rejecting predictions to obtain reliable models in healthcare
by: Valeriano, Maria Gabriela, et al.
Published: (2025)

Deep classifier kriging for probabilistic spatial prediction of air quality index
by: Chen, Junyu, et al.
Published: (2025)

Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents
by: Lee, Jane H., et al.
Published: (2025)

Explainable assessment of financial experts' credibility by classifying social media forecasts and checking the predictions with actual market data
by: García-Méndez, Silvia, et al.
Published: (2024)

Combining Minkowski and Chebyshev: New distance proposal and survey of distance metrics using k-nearest neighbours classifier
by: Rodrigues, Érick Oliveira
Published: (2021)

The Illusion of Certainty: Decoupling Capability and Calibration in On-Policy Distillation
by: Zhang, Jiaxin, et al.
Published: (2026)

Optimized Certainty Equivalent Risk-Controlling Prediction Sets
by: Huang, Jiayi, et al.
Published: (2026)

The Confidence Trap: Gender Bias and Predictive Certainty in LLMs
by: Sabir, Ahmed, et al.
Published: (2026)

Certainty in Uncertainty: Reasoning over Uncertain Knowledge Graphs with Statistical Guarantees
by: Zhu, Yuqicheng, et al.
Published: (2025)

XNB: Explainable Class-Specific NaIve-Bayes Classifier
by: Aguilar-Ruiz, Jesus S., et al.
Published: (2024)

Behavior of prediction performance metrics with rare events
by: Minus, Emily, et al.
Published: (2025)

LxCIM: a new rank-based binary classifier performance metric invariant to local exchange of classes
by: Brogueira, Tiago, et al.
Published: (2025)

The Over-Certainty Phenomenon in Modern Test-Time Adaptation Algorithms
by: Amin, Fin, et al.
Published: (2024)

On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents
by: Mortensen, Oliver, et al.
Published: (2026)

The Illusion of Certainty: Uncertainty Quantification for LLMs Fails under Ambiguity
by: Tomov, Tim, et al.
Published: (2025)

A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
by: Wang, Kaiwen, et al.
Published: (2024)

A View of the Certainty-Equivalence Method for PAC RL as an Application of the Trajectory Tree Method
by: Kalyanakrishnan, Shivaram, et al.
Published: (2025)

Global explainability of a deep abstaining classifier
by: Dhaubhadel, Sayera, et al.
Published: (2025)

Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
by: Wang, Shenhao, et al.
Published: (2021)

Parametric $ρ$-Norm Scaling Calibration
by: Zhang, Siyuan, et al.
Published: (2024)

Certainty-Validity: A Diagnostic Framework for Discrete Commitment Systems
by: Anderson, Datorien L.
Published: (2026)

Application of the representative measure approach to assess the reliability of decision trees in dealing with unseen vehicle collision data
by: Perera-Lago, Javier, et al.
Published: (2024)

SGC-RML: A reliable and interpretable longitudinal assessment for PD in real-world DNS
by: Wei, Wenbin, et al.
Published: (2026)

Towards providing reliable job completion time predictions using PCS
by: Faisal, Abdullah Bin, et al.
Published: (2024)

Zero-failure testing of binary classifiers
by: Ivrissimtzis, Ioannis, et al.
Published: (2024)

GT-CausIn: a novel causal-based insight for traffic prediction
by: Gao, Ting, et al.
Published: (2022)

Deep learning the Hurst parameter of linear fractional processes and assessing its reliability
by: Boros, Dániel, et al.
Published: (2024)