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cs.LG2026
Robust Ambiguity Detection (RAD) From Model- and Feature-Space Consistency
Manya Singh, Mark T. Keane, Arjun Pakrashi
Machine learning models should be robust, in the sense of remaining predictively consistent under permissible variations. A model's predictions should ideally remain unchanged when…
cs.LG2022
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ
Eoin Delaney, Arjun Pakrashi, Derek Greene +1
Counterfactual explanations have emerged as a popular solution for the eXplainable AI (XAI) problem of elucidating the predictions of black-box deep-learning systems due to their p…
cs.LG2021★ 3 cited
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation
Mohammed Temraz, Mark T. Keane
Learning from class imbalanced datasets poses challenges for many machine learning algorithms. Many real-world domains are, by definition, class imbalanced by virtue of having a ma…