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Results: 23
Number of items: 23
  • Open Access
    Röber, T. E. (2026). Interpretable machine learning: Optimization-based explanations and human-centered evaluation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kurtz, J., Birbil, Ş. İ., & den Hertog, D. (2026). Counterfactual explanations for linear optimization. European Journal of Operational Research, 329(1), 24-41. https://doi.org/10.1016/j.ejor.2025.06.016
  • Open Access
    Röber, T. E., Lumadjeng, A. C., Akyuz, M. H., & Birbil, S. İ. B. (2025). Rule generation for classification: Scalability, interpretability, and fairness. Computers & Operations Research, 183, Article 107163. https://doi.org/10.1016/j.cor.2025.107163
  • Open Access
    Röber, T. E., Goedhart, R., & Birbil, Ş. İ. (2025). Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare. Proceedings of Machine Learning Research, 298. https://proceedings.mlr.press/v298/rober25a.html
  • Open Access
    Cinà, G., Röber, T. E., Goedhart, R., & Birbil, Ş. İ. (2025). Why we do need explainable AI for healthcare. Diagnostic and Prognostic Research, 9, Article 24. https://doi.org/10.1186/s41512-025-00209-4
  • Open Access
    Wasserkrug, S., Boussioux, L., den Hertog, D., Mirzazadeh, F., Birbil, Ş. I., Kurtz, J., & Maragno, D. (2025). Enhancing decision making through the integration of large language models and operations research optimization. In T. Walsh, J. Shah, & Z. Kolter (Eds.), Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence: February 25-March 4, 2025, Philadelphia, Pennsylvania, USA (Vol. 27, pp. 28643-28650). AAAI Press. https://doi.org/10.1609/aaai.v39i27.35090
  • Open Access
    Maragno, D., Wiberg, H., Bertsimas, D., Birbil, S. I., den Hertog, D., & Fajemisin, A. O. (2025). Mixed-Integer Optimization with Constraint Learning. Operations Research, 73(2), 1011-1028. https://doi.org/10.1287/opre.2021.0707
  • Open Access
    Boon, C., Durak, E., & Birbil, Ş. İ. (2025). Towards a better understanding of misfit through explainable AI techniques. In J. Billsberry, & D. L. Talbot (Eds.), Employee Misfit: Theories, Perspectives, and New Directions (pp. 223–245). Springer. https://doi.org/10.1007/978-981-96-8208-9_12
  • Open Access
    Maragno, D. (2025). Optimization with constraint learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Vogels, L., Mohammadi, R., Schoonhoven, M., Birbil, Ş. I., Dyrba, M., & Alzheimer's Disease Neuroimaging Initiative (2025). Modeling Alzheimer’s disease: Bayesian copula graphical model from demographic, cognitive, and neuroimaging data. Journal of Alzheimer's Disease, 108(1, supplement), S244-S257. https://doi.org/10.1177/13872877251337944
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