19 citations · 37 across the 7 of their papers we have counts for
4 papers · 1 filter
Output-Constrained Decision Trees
Hüseyin Tunç, Doğanay Özese, Ş. İlker Birbil +3
Incorporating domain-specific constraints into machine learning models is essential for generating predictions that are both accurate and feasible in real-world applications. This…
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…
Optimization with Constraint Learning: A Framework and Survey
Adejuyigbe Fajemisin, Donato Maragno, Dick den Hertog
Many real-life optimization problems frequently contain one or more constraints or objectives for which there are no explicit formulas. If data is however available, these data can…