19 citations · 72 across the 23 of their papers we have counts for
4 papers · 1 filter
Linear Model Extraction via Factual and Counterfactual Queries
Daan Otto, Jannis Kurtz, Dick den Hertog +1
In model extraction attacks, the goal is to reveal the parameters of a black-box machine learning model by querying the model for a selected set of data points. Due to an increasin…
Counterfactual Explanations for Linear Optimization
Jannis Kurtz, Ş. İlker Birbil, Dick den Hertog
The concept of counterfactual explanations (CE) has emerged as one of the important concepts to understand the inner workings of complex AI systems. In this paper, we translate the…
Machine Learning for K-adaptability in Two-stage Robust Optimization
Esther Julien, Krzysztof Postek, Ş. İlker Birbil
Two-stage robust optimization problems constitute one of the hardest optimization problem classes. One of the solution approaches to this class of problems is K-adaptability. This…
Mixed-Integer Optimization with Constraint Learning
Donato Maragno, Holly Wiberg, Dimitris Bertsimas +3
We establish a broad methodological foundation for mixed-integer optimization with learned constraints. We propose an end-to-end pipeline for data-driven decision making in which c…