Marco Favier

According to our database, Marco Favier authored at least 7 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Cherry on the cake: fairness is NOT an optimization problem.

Marco Favier, Toon Calders

Mach. Learn., July, 2025

From Implicit to Explicit Assumptions: Why There is No Fairness Without Bias-Awareness.

Marco Favier, Toon Calders

Proceedings of the European Workshop on Algorithmic Fairness, 2025

What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems.

Jens Leysen, Marco Favier, Bart Goethals

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

"Patriarchy Hurts Men Too." Does Your Model Agree? A Discussion on Fairness Assumptions.

Marco Favier, Toon Calders

CoRR, 2024

How to Be Fair? a Discussion and Future Perspectives.

Marco Favier, Toon Calders

Proceedings of the 3rd European Workshop on Algorithmic Fairness, 2024

2023

How to be fair? A study of label and selection bias.

Marco Favier, Toon Calders, Sam Pinxteren, Jonathan Meyer

Mach. Learn., December, 2023

2022

RangeGrad: Explaining Neural Networks by Measuring Uncertainty Through Bound Propagation.

Sam Pinxteren, Marco Favier, Toon Calders

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022