2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
Robust Counterfactual Explanations in Machine Learning: A Survey
Junqi Jiang, Francesco Leofante, Antonio Rago +1
Counterfactual explanations (CEs) are advocated as being ideally suited to providing algorithmic recourse for subjects affected by the predictions of machine learning models. While…
cs.LG2024
Recourse under Model Multiplicity via Argumentative Ensembling (Technical Report)
Junqi Jiang, Antonio Rago, Francesco Leofante +1
Model Multiplicity (MM) arises when multiple, equally performing machine learning models can be trained to solve the same prediction task. Recent studies show that models obtained…