T.E. (Tabea) Röber
Faculteit Economie en Bedrijfskunde
Sectie Business Analytics
Bezoekadres
- Plantage Muidergracht 12
- Kamernummer: M 4.04
Postadres
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Postbus 15953
1001 NL Amsterdam
Contactgegevens
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Publicaties
2024
- Maragno, D., Röber, T. E., Kurtz, J., Goedhart, R., Birbil, S. I., & den Hertog, D. (2024). Finding regions of counterfactual explanations via robust optimization. INFORMS Journal on Computing. Advance online publication. https://doi.org/10.1287/ijoc.2023.0153
2023
Cina, G., Röber, T. E., Goedhart, R., & Birbil, S. I. (2023). Semantic match: Debugging feature attribution methods in XAI for healthcare. Proceedings of Machine Learning Research, 209, 182-191. https://proceedings.mlr.press/v209/cina23a.html [details]
2022
- Lumadjeng, A. C., Röber, T. E., Akyuz, H., & Birbil, S. I. (2022). Rule Generation for Classification: Scalability, Interpretability, and Fairness. Manuscript submitted for publication.
- Maragno, D., Röber, T. E., & Birbil, S. İ. (2022). Counterfactual Explanations Using Optimization With Constraint Learning. In OPT2022: Optimization for Machine Learning. Accepted papers OPT-ML. https://doi.org/10.48550/arXiv.2209.10997 [details]
2022
- Cina, G., Röber, T., Goedhart, R., & Birbil, I. (2022). Why we do need Explainable AI for Healthcare. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2206.15363 [details]
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Nevenwerkzaamheden
Geen nevenwerkzaamheden
Cina, G., Röber, T. E., Goedhart, R., & Birbil, S. I. (2023). Semantic match: Debugging feature attribution methods in XAI for healthcare. Proceedings of Machine Learning Research, 209, 182-191.