Wissenschaftliche Artikel

Schidler, A., & Szeider, S. (2024). SAT-based Decision Tree Learning for Large Data Sets. Journal of Artificial Intelligence Research, 80, 875–918. https://doi.org/10.1613/jair.1.15956 ( reposiTUm)
Ordyniak, S., Schidler, A., & Szeider, S. (2024). Backdoor DNFs. Journal of Computer and System Sciences, 144, Article 103547. https://doi.org/10.1016/j.jcss.2024.103547 ( reposiTUm)
Schidler, A., & Szeider, S. (2023). SAT-boosted tabu search for coloring massive graphs. ACM Journal on Experimental Algorithmics, 28, Article 1.5. https://doi.org/10.1145/3603112 ( reposiTUm)
Schidler, A., & Szeider, S. (2023). Computing optimal hypertree decompositions with SAT. Artificial Intelligence, 325, Article 104015. https://doi.org/10.1016/j.artint.2023.104015 ( reposiTUm)

Beiträge in Tagungsbänden

Schidler, A., & Szeider, S. (2023). Computing Twin-width with SAT and Branch & Bound. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 2013–2021). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/224 ( reposiTUm)
Ramaswamy, V. P., & Szeider, S. (2023). Proven Optimally-Balanced Latin Rectangles with SAT. In R. Yap (Ed.), 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Schloss-Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CP.2023.48 ( reposiTUm)