14 citations · 23 across the 5 of their papers we have counts for
3 papers · 1 filter
Finding Regions of Counterfactual Explanations via Robust Optimization
Donato Maragno, Jannis Kurtz, Tabea E. Röber +3
Counterfactual explanations play an important role in detecting bias and improving the explainability of data-driven classification models. A counterfactual explanation (CE) is a m…
Counterfactual Explanations Using Optimization With Constraint Learning
Donato Maragno, Tabea E. Röber, Ilker Birbil
To increase the adoption of counterfactual explanations in practice, several criteria that these should adhere to have been put forward in the literature. We propose counterfactual…
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Tabea E. Röber, Adia C. Lumadjeng, M. Hakan Akyüz +1
We introduce a new rule-based optimization method for classification with constraints. The proposed method leverages column generation for linear programming, and hence, is scalabl…