5 papers
Multiple Jump MCMC: A Scalable Algorithm for Bayesian Inference on Binary Model Spaces
Lucas Vogels, Reza Mohammadi, Marit Schoonhoven +2
This article considers Bayesian model inference on binary model spaces. Binary model spaces are used by a large class of models, including graphical models, variable selection, mix…
The Role of Feature Interactions in Graph-based Tabular Deep Learning
Elias Dubbeldam, Reza Mohammadi, Marit Schoonhoven +1
Accurate predictions on tabular data rely on capturing complex, dataset-specific feature interactions. Attention-based methods and graph neural networks, referred to as graph-based…
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…
Learning with Subset Stacking
Å. Ä°lker Birbil, Sinan Yıldırım, Samet Ãopur +1
We propose a new regression algorithm that learns from a set of input-output pairs. Our algorithm is designed for populations where the relation between the input variables and the…
Coherent Local Explanations for Mathematical Optimization
Daan Otto, Jannis Kurtz, S. Ilker Birbil
The surge of explainable artificial intelligence methods seeks to enhance transparency and explainability in machine learning models. At the same time, there is a growing demand fo…