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2020 – today
- 2024
[j1]Maarten Buyl
, Tijl De Bie:
Inherent Limitations of AI Fairness. Commun. ACM 67(2): 48-55 (2024)- [c7]Maarten Buyl, MaryBeth Defrance, Tijl De Bie:
fairret: a Framework for Differentiable Fairness Regularization Terms. ICLR 2024 - [c6]Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie:
KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces. ECML/PKDD (8) 2024: 409-412 - [i12]Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie:
KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces. CoRR abs/2404.17597 (2024) - [i11]Raphaël Romero, Maarten Buyl, Tijl De Bie, Jefrey Lijffijt:
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms. CoRR abs/2405.17182 (2024) - [i10]MaryBeth Defrance, Maarten Buyl, Tijl De Bie:
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods. CoRR abs/2409.16965 (2024) - [i9]Maarten Buyl, Alexander Rogiers, Sander Noels, Iris Dominguez-Catena, Edith Heiter, Raphaël Romero, Iman Johary, Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie:
Large Language Models Reflect the Ideology of their Creators. CoRR abs/2410.18417 (2024) - [i8]Alexander Rogiers, Sander Noels, Maarten Buyl, Tijl De Bie:
Persuasion with Large Language Models: a Survey. CoRR abs/2411.06837 (2024) - 2023
- [c5]Maarten Buyl, Paul Missault, Pierre-Antoine Sondag:
RankFormer: Listwise Learning-to-Rank Using Listwide Labels. KDD 2023: 3762-3773 - [i7]Maarten Buyl, Paul Missault, Pierre-Antoine Sondag:
RankFormer: Listwise Learning-to-Rank Using Listwide Labels. CoRR abs/2306.05808 (2023) - [i6]Maarten Buyl, MaryBeth Defrance, Tijl De Bie:
fairret: a Framework for Differentiable Fairness Regularization Terms. CoRR abs/2310.17256 (2023) - 2022
- [c4]Maarten Buyl, Christina Cociancig, Cristina Frattone, Nele Roekens:
Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical Analysis. FAccT 2022: 1071-1082 - [c3]Maarten Buyl, Tijl De Bie:
Optimal Transport of Classifiers to Fairness. NeurIPS 2022 - [i5]Maarten Buyl, Tijl De Bie:
Optimal Transport of Binary Classifiers to Fairness. CoRR abs/2202.03814 (2022) - [i4]Maarten Buyl, Christina Cociancig, Cristina Frattone, Nele Roekens:
Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical Analysis. CoRR abs/2206.06149 (2022) - [i3]Maarten Buyl, Tijl De Bie:
Inherent Limitations of AI Fairness. CoRR abs/2212.06495 (2022) - 2021
- [c2]Maarten Buyl, Tijl De Bie:
The KL-Divergence Between a Graph Model and its Fair I-Projection as a Fairness Regularizer. ECML/PKDD (2) 2021: 351-366 - [i2]Maarten Buyl, Tijl De Bie:
The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer. CoRR abs/2103.01846 (2021) - 2020
- [c1]Maarten Buyl, Tijl De Bie:
DeBayes: a Bayesian Method for Debiasing Network Embeddings. ICML 2020: 1220-1229 - [i1]Maarten Buyl, Tijl De Bie:
DeBayes: a Bayesian method for debiasing network embeddings. CoRR abs/2002.11442 (2020)
Coauthor Index
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