Jens Leysen

Orcid: 0000-0003-2561-0932

According to our database¹, Jens Leysen authored at least 4 papers between 2022 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Bibliography

2025

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

[BibT_eX]

[DOI]

Jens Leysen

Marco Favier

Bart Goethals

CoRR, August, 2025

2023

How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News.

[BibT_eX]

[DOI]

Lien Michiels

Jorre T. A. Vannieuwenhuyze

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Exploring Unlearning Methods to Ensure the Privacy, Security, and Usability of Recommender Systems.

[BibT_eX]

[DOI]

Jens Leysen

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work.

[BibT_eX]

[DOI]

Proceedings of the UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4, 2022

Jens Leysen

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