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Researcher
Maarten Buyl
Profile
Projects
Publications
Activities
Awards & Distinctions
15
Results
2024
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
Marybeth Defrance
Maarten Buyl
Tijl De Bie
U
Conference
2024
BiMi sheets for bias mitigation methods
Marybeth Defrance
Maarten Buyl
Guillaume Bied
Jefrey Lijffijt
Tijl De Bie
C3
Conference
2024
Exploring the performance of continuous-time dynamic link prediction algorithms
Raphaël Romero
Maarten Buyl
Tijl De Bie
Jefrey Lijffijt
A1
Journal Article
in
APPLIED SCIENCES-BASEL
2024
FAIRRET : a framework for differentiable fairness regularization terms
Maarten Buyl
Marybeth Defrance
Tijl De Bie
C1
Conference
2024
Inherent limitations of AI fairness
Maarten Buyl
Tijl De Bie
A1
Journal Article
in
COMMUNICATIONS OF THE ACM
2024
KamerRaad : enhancing information retrieval in Belgian national politics through hierarchical summarization and conversational interfaces
Alexander Rogiers
Maarten Buyl
Bo Kang
Tijl De Bie
P1
Conference
2024
fairret : a framework for differentiable fairness regularization terms
Marybeth Defrance
Maarten Buyl
Tijl De Bie
C1
Conference
2024
2023
Fairness regularization in machine learning : methods and limitations
Maarten Buyl
Tijl De Bie
Jefrey Lijffijt
Dissertation
2023
Fairret : a framework for differentiable fairness regularization terms
Maarten Buyl
Marybeth Defrance
Tijl De Bie
Preprint
2023
RankFormer : listwise learning-to-rank using listwide labels
Maarten Buyl
Paul Missault
Pierre-Antoine Sondag
P1
Conference
2023
2022
Inherent limitations of AI fairness
Maarten Buyl
Tijl De Bie
Preprint
2022
Optimal transport of classifiers to fairness
Maarten Buyl
Tijl De Bie
C1
Conference
2022
Tackling algorithmic disability discrimination in the hiring process : an ethical, legal and technical analysis
Maarten Buyl
Christina Cociancig
Cristina Frattone
Nele Roekens
C1
Conference
2022
2021
The KL-divergence between a graph model and its fair I-projection as a fairness regularizer
Maarten Buyl
Tijl De Bie
P1
Conference
2021
2020
DeBayes : a Bayesian method for debiasing network embeddings
Maarten Buyl
Tijl De Bie
P1
Conference
2020