Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple…
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecastingby Daniel Iong,…
DAGnosis: Localized Identification of Data Inconsistencies using Structuresby Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan…
Does Negative Sampling Matter? A Review with Insights into its Theory and Applicationsby Zhen Yang,…
An Interpretable Evaluation of Entropy-based Novelty of Generative Modelsby Jingwei Zhang, Cheuk Ting Li, Farzan…
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyondby Kyriakos Axiotis, Vincent Cohen-Addad, Monika…
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updatesby Daniele Angioni, Luca Demetrio, Maura Pintor,…
Adversarial Perturbations of Physical Signalsby Robert L. Bassett, Austin Van Dellen, Anthony P. AustinFirst submitted…
LCEN: A Novel Feature Selection Algorithm for Nonlinear, Interpretable Machine Learning Modelsby Pedro Seber, Richard…
Achievable Fairness on Your Data With Utility Guaranteesby Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang LiuFirst…