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Información - Algorithmic Recourse
Enhancing User Experience in Interactive and Personalized Algorithmic Recourse
Algorithmic recourse aims to provide actionable suggestions to overturn unfavorable decisions made by automated machine learning models. This work investigates a guided-interaction paradigm that combines preference elicitation with algorithmic recourse to personalize the recourse plans and improve the user experience.
Understanding Non-Adversarial Algorithmic Recourse in Machine Learning
Non-adversarial recourse is crucial in high-stakes decision-making scenarios, requiring alignment with ground truth labels.
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