no code implementations • 22 Apr 2024 • Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie
KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information.
1 code implementation • 26 Oct 2023 • Maarten Buyl, MaryBeth Defrance, Tijl De Bie
Current fairness toolkits in machine learning only admit a limited range of fairness definitions and have seen little integration with automatic differentiation libraries, despite the central role these libraries play in modern machine learning pipelines.
1 code implementation • 9 Jun 2023 • Maarten Buyl, Paul Missault, Pierre-Antoine Sondag
Web applications where users are presented with a limited selection of items have long employed ranking models to put the most relevant results first.
1 code implementation • 8 Feb 2022 • Maarten Buyl, Tijl De Bie
In past work on fairness in machine learning, the focus has been on forcing the prediction of classifiers to have similar statistical properties for people of different demographics.
1 code implementation • 2 Mar 2021 • Maarten Buyl, Tijl De Bie
Given this, we propose a fairness regularizer defined as the KL-divergence between the graph model and its I-projection onto the set of fair models.
1 code implementation • ICML 2020 • Maarten Buyl, Tijl De Bie
As machine learning algorithms are increasingly deployed for high-impact automated decision making, ethical and increasingly also legal standards demand that they treat all individuals fairly, without discrimination based on their age, gender, race or other sensitive traits.