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Results: 17
Number of items: 17
  • 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. (2026). Interpretable machine learning: Optimization-based explanations and human-centered evaluation. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
    Maragno, D. (2025). Optimization with constraint learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Vogels, L., Mohammadi, R., Schoonhoven, M., & Birbil, Ş. İ. (2024). Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison [Data set]. Taylor & Francis. https://doi.org/10.6084/m9.figshare.26880600.v1
  • Open Access
    Maragno, D., Buti, G., Birbil, S. I., Liao, Z., Bortfeld, T., den Hertog, D., & Ajdari, A. (2024). Embedding machine learning based toxicity models within radiotherapy treatment plan optimization. Physics in Medicine and Biology, 69(7), Article 075003. https://doi.org/10.1088/1361-6560/ad2d7e
  • Open Access
    von Stackelberg, P., Goedhart, R., Birbil, S. I., & Does, R. J. M. M. (2024). Comparison of threshold tuning methods for predictive monitoring. Quality and Reliability Engineering International, 40(1), 499-512. https://doi.org/10.1002/qre.3436
  • Open Access
    Maragno, D., Kurtz, J., Röber, T. E., Goedhart, R., Birbil, Ş. İ., & den Hertog, D. (2024). Finding regions of counterfactual explanations via robust optimization. INFORMS Journal on Computing, 36(5), 1316–1334. https://doi.org/10.1287/ijoc.2023.0153
  • Open Access
    Birbil, İ., Martin, Ö., Onay, G., & Öztoprak, F. (2024). Bolstering stochastic gradient descent with model building. TOP, 32(3), 517-536. https://doi.org/10.1007/s11750-024-00673-z
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