Kirchweger, M., & Szeider, S. (2024). SAT Modulo Symmetries for Graph Generation and Enumeration. ACM Transactions on Computational Logic, 25(3), Article 18. https://doi.org/10.1145/3670405 ( reposiTUm)

Dreier, J., Ordyniak, S., & Szeider, S. (2024). SAT backdoors: Depth beats size. Journal of Computer and System Sciences, 142, Article 103520. https://doi.org/10.34726/8101 ( reposiTUm)

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)

Fazekas, K., Niemetz, A., Preiner, M., Kirchweger, M., Szeider, S., & Biere, A. (2024). Satisfiability Modulo User Propagators. Journal of Artificial Intelligence Research, 81, 989–1017. https://doi.org/10.1613/jair.1.16163 ( reposiTUm)

Dreier, J., Ordyniak, S., & Szeider, S. (2023). CSP beyond tractable constraint languages. Constraints, 28(3), 450–471. https://doi.org/10.1007/s10601-023-09362-3 ( 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)

Peitl, T., & Szeider, S. (2023). Are hitting formulas hard for resolution? Discrete Applied Mathematics, 337, 173–184. https://doi.org/10.1016/j.dam.2023.05.003 ( reposiTUm)

Fichte, J. K., Le Berre, D., Hecher, M., & Szeider, S. (2023). The silent (r)evolution of SAT. Communications of the ACM, 66(6), 64–72. https://doi.org/10.1145/3560469 ( reposiTUm)

Eiben, E., Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2023). On the parameterized complexity of clustering problems for incomplete data. Journal of Computer and System Sciences, 134, 1–19. https://doi.org/10.1016/j.jcss.2022.12.001 ( reposiTUm)

Ganian, R., Schidler, A., Sorge, M., & Szeider, S. (2022). Threshold Treewidth and Hypertree Width. Journal of Artificial Intelligence Research, 74, 1687–1713. https://doi.org/10.1613/JAIR.1.13661 ( reposiTUm)

Ganian, R., Kim, E. J., & Szeider, S. (2022). Algorithmic applications of tree-cut width. SIAM Journal on Discrete Mathematics, 36(4), 2635–2666. https://doi.org/10.1137/20M137478X ( reposiTUm)

Ganian, R., Kim, E. J., Slivovsky, F., & Szeider, S. (2022). Sum-of-Products with Default Values: Algorithms and Complexity Results. Journal of Artificial Intelligence Research, 73, 535–552. https://doi.org/10.1613/JAIR.1.12370 ( reposiTUm)

Ganian, R., & Szeider, S. (2021). New width parameters for SAT and #SAT. Artificial Intelligence, 295(103460), 103460. https://doi.org/10.1016/j.artint.2021.103460 ( reposiTUm)

Ganian, R., Haan, R. de, Kanj, I., & Szeider, S. (2020). On Existential MSO and Its Relation to ETH. ACM Transactions on Computation Theory, 12(4), 1–32. https://doi.org/10.1145/3417759 ( reposiTUm)

Haan, R. de, & Szeider, S. (2019). A Compendium of Parameterized Problems at Higher Levels of the Polynomial Hierarchy. Algorithms, 12(9), 188. https://doi.org/10.3390/a12090188 ( reposiTUm)

Lodha, N., Ordyniak, S., & Szeider, S. (2019). A SAT Approach to Branchwidth. ACM Transactions on Computational Logic, 20(3), 1–24. https://doi.org/10.1145/3326159 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2019). Dependency Learning for QBF. Journal of Artificial Intelligence Research, 65, 181–208. https://doi.org/10.1613/jair.1.11529 ( reposiTUm)

Paulusma, D., & Szeider, S. (2019). On the parameterized complexity of (k, s)-SAT. Information Processing Letters, 143, 34–36. https://doi.org/10.1016/j.ipl.2018.11.005 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2019). Long-Distance Q-Resolution with Dependency Schemes. Journal of Automated Reasoning, 63(1), 127–155. https://doi.org/10.1007/s10817-018-9467-3 ( reposiTUm)

Eiben, E., Ganian, R., & Szeider, S. (2018). Meta-kernelization using well-structured modulators. Discrete Applied Mathematics, 248, 153–167. https://doi.org/10.1016/j.dam.2017.09.018 ( reposiTUm)

Eiben, E., Ganian, R., & Szeider, S. (2017). Solving Problems on Graphs of High Rank-Width. Algorithmica, 80(2), 742–771. https://doi.org/10.1007/s00453-017-0290-8 ( reposiTUm)

Haan, R. D., Kanj, I., & Szeider, S. (2017). On the Parameterized Complexity of Finding Small Unsatisfiable Subsets of CNF Formulas and CSP Instances. ACM Transactions on Computational Logic, 18(3), 1–46. https://doi.org/10.1145/3091528 ( reposiTUm)

Ganian, R., Ramanujan, M. S., & Szeider, S. (2017). Discovering Archipelagos of Tractability for Constraint Satisfaction and Counting. ACM Transactions on Algorithms, 13(2), 1–32. https://doi.org/10.1145/3014587 ( reposiTUm)

de Haan, R., & Szeider, S. (2017). Parameterized complexity classes beyond para-NP. Journal of Computer and System Sciences, 87, 16–57. https://doi.org/10.1016/j.jcss.2017.02.002 ( reposiTUm)

Gaspers, S., Misra, N., Ordyniak, S., Szeider, S., & Živný, S. (2017). Backdoors into heterogeneous classes of SAT and CSP. Journal of Computer and System Sciences, 85, 38–56. https://doi.org/10.1016/j.jcss.2016.10.007 ( reposiTUm)

Müller, M., & Szeider, S. (2017). The Treewidth of Proofs. Information and Computation, 255, 147–164. http://hdl.handle.net/20.500.12708/147673 ( reposiTUm)

Bova, S., Ganian, R., & Szeider, S. (2016). Quantified conjunctive queries on partially ordered sets. Theoretical Computer Science, 618, 72–84. https://doi.org/10.1016/j.tcs.2016.01.010 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2016). Soundness of Q-resolution with dependency schemes. Theoretical Computer Science, 612, 83–101. https://doi.org/10.1016/j.tcs.2015.10.020 ( reposiTUm)

Gaspers, S., Ordyniak, S., Ramanujan, M. S., Saurabh, S., & Szeider, S. (2016). Backdoors to q-Horn. Algorithmica, 74(1), 540–557. https://doi.org/10.1007/s00453-014-9958-5 ( reposiTUm)

Ganian, R., Slivovsky, F., & Szeider, S. (2016). Meta-kernelization with structural parameters. Journal of Computer and System Sciences, 82(2), 333–346. https://doi.org/10.1016/j.jcss.2015.08.003 ( reposiTUm)

Gaspers, S., Koivisto, M., Liedloff, M., Ordyniak, S., & Szeider, S. (2015). On finding optimal polytrees. Theoretical Computer Science, 592, 49–58. https://doi.org/10.1016/j.tcs.2015.05.012 ( reposiTUm)

Bova, S., Ganian, R., & Szeider, S. (2015). Model Checking Existential Logic on Partially Ordered Sets. ACM Transactions on Computational Logic, 17(2), 1–35. https://doi.org/10.1145/2814937 ( reposiTUm)

Paulusma, D., Slivovsky, F., & Szeider, S. (2015). Model Counting for CNF Formulas of Bounded Modular Treewidth. Algorithmica, 76(1), 168–194. https://doi.org/10.1007/s00453-015-0030-x ( reposiTUm)

Kanj, I., & Szeider, S. (2015). Parameterized and subexponential-time complexity ofsatisfiability problems and applications. Theoretical Computer Science, 607, 282–295. https://doi.org/10.1016/j.tcs.2015.08.029 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2015). Quantifier Reordering for QBF. Journal of Automated Reasoning, 56(4), 459–477. https://doi.org/10.1007/s10817-015-9353-1 ( reposiTUm)

Fichte, J. K., & Szeider, S. (2015). Backdoors to tractable answer-set programming. Artificial Intelligence, 220, 64–103. https://doi.org/10.1016/j.artint.2014.12.001 ( reposiTUm)

Fichte, J. K., & Szeider, S. (2015). Backdoors to Normality for Disjunctive Logic Programs. ACM Transactions on Computational Logic, 17(1), 1–23. https://doi.org/10.1145/2818646 ( reposiTUm)

Heule, M. J. H., & Szeider, S. (2015). A SAT Approach to Clique-Width. ACM Transactions on Computational Logic, 16(3), 1–27. https://doi.org/10.1145/2736696 ( reposiTUm)

De Haan, R., Kanj, I., & Szeider, S. (2015). On the Subexponential-Time Complexity of CSP. Journal of Artificial Intelligence Research, 52, 203–234. https://doi.org/10.1613/jair.4540 ( reposiTUm)

Bäckström, C., Jonsson, P., Ordyniak, S., & Szeider, S. (2015). A Complete Parameterized Complexity Analysis of Bounded Planning. Journal of Computer and System Sciences, 81(7), 1311–1332. https://doi.org/10.1016/j.jcss.2015.04.002 ( reposiTUm)

Gaspers, S., & Szeider, S. (2014). Guarantees and limits of preprocessing in constraint satisfaction and reasoning. Artificial Intelligence, 216, 1–19. https://doi.org/10.1016/j.artint.2014.06.006 ( reposiTUm)

Ordyniak, S., & Szeider, S. (2013). Parameterized Complexity Results for Exact Bayesian Network Structure Learning. Journal of Artificial Intelligence Research, 46, 263–302. https://doi.org/10.1613/jair.3744 ( reposiTUm)

Ordyniak, S., Paulusma, D., & Szeider, S. (2013). Satisfiability of acyclic and almost acyclic CNF formulas. Theoretical Computer Science, 481, 85–99. https://doi.org/10.1016/j.tcs.2012.12.039 ( reposiTUm)

Dvořák, W., Ordyniak, S., & Szeider, S. (2012). Augmenting Tractable Fragments of Abstract Argumentation. Artificial Intelligence, 186, 157–173. https://doi.org/10.1016/j.artint.2012.03.002 ( reposiTUm)

van ’t Hof, P., Kamiński, M., Paulusma, D., Szeider, S., & Thilikos, D. M. (2012). On Graph Contractions and Induced Minors. Discrete Applied Mathematics, 160(6), 799–809. https://doi.org/10.1016/j.dam.2010.05.005 ( reposiTUm)

Mathieson, L., & Szeider, S. (2012). Editing Graphs to Satisfy Degree Constraints: A Parameterized Approach. Journal of Computer and System Sciences, 78(1), 179–191. https://doi.org/10.1016/j.jcss.2011.02.001 ( reposiTUm)

PICHLER, R., RÜMMELE, S., SZEIDER, S., & WOLTRAN, S. (2012). Tractable Answer-Set Programming with Weight Constraints: Bounded Treewidth is not Enough. Theory and Practice of Logic Programming, 14(2), 141–164. https://doi.org/10.1017/s1471068412000099 ( reposiTUm)

Gutin, G., Kim, E. J., Soleimanfallah, A., Szeider, S., & Yeo, A. (2012). Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming. Algorithmica, 64(1), 112–125. https://doi.org/10.1007/s00453-011-9548-8 ( reposiTUm)

Alon, N., Gutin, G., Kim, E. J., Szeider, S., & Yeo, A. (2011). Solving MAX-r-SAT Above a Tight Lower Bound. Algorithmica, 61(3), 638–655. https://doi.org/10.1007/s00453-010-9428-7 ( reposiTUm)

Dantchev, S. S., Martin, B., & Szeider, S. (2011). Parameterized Proof Complexity. Computational Complexity, 20(1), 51–85. http://hdl.handle.net/20.500.12708/162514 ( reposiTUm)

Kim, E. J., Ordyniak, S., & Szeider, S. (2011). Algorithms and Complexity Results for Persuasive Argumentation. Artificial Intelligence, 175(9–10), 1722–1736. https://doi.org/10.1016/j.artint.2011.03.001 ( reposiTUm)

Fellows, M. R., Fomin, F. V., Lokshtanov, D., Rosamond, F., Saurabh, S., Szeider, S., & Thomassen, C. (2011). On the Complexity of Some Colorful Problems Parameterized by Treewidth. Information and Computation, 209(2), 143–153. https://doi.org/10.1016/j.ic.2010.11.026 ( reposiTUm)

Szeider, S. (2011). Monadic Second Order Logic on Graphs with Local Cardinality Constraints. ACM Transactions on Computational Logic, 12(2), 1–21. https://doi.org/10.1145/1877714.1877718 ( reposiTUm)

Szeider, S. (2011). The Parameterized Complexity of k-Flip Local Search for SAT and MAX SAT. Discrete Optimization, 8(1), 139–145. http://hdl.handle.net/20.500.12708/162540 ( reposiTUm)

Samer, M., & Szeider, S. (2011). Tractable Cases of the Extended Global Cardinality Constraint. Constraints, 16(1), 1–24. https://doi.org/10.1007/s10601-009-9079-y ( reposiTUm)

Gutin, G., Kim, E. J., Szeider, S., & Yeo, A. (2011). A Probabilistic Approach to Problems Parameterized Above or Below Tight Bounds. Journal of Computer and System Sciences, 77(2), 422–429. https://doi.org/10.1016/j.jcss.2010.06.001 ( reposiTUm)

Broersma, H., Dantchev, S. S., Johnson, M., & Szeider, S. (2010). Journal of Discrete Algorithms 8(2) - Editorial. Journal of Discrete Algorithms, 8(2), iii–iv. https://doi.org/10.1016/s1570-8667(10)00008-0 ( reposiTUm)

Samer, M., & Szeider, S. (2010). Constraint Satisfaction with Bounded Treewidth Revisited. Journal of Computer and System Sciences, 76(2), 103–114. https://doi.org/10.1016/j.jcss.2009.04.003 ( reposiTUm)

Samer, M., & Szeider, S. (2010). Algorithms for Propositional Model Counting. Journal of Discrete Algorithms, 8(1), 50–64. https://doi.org/10.1016/j.jda.2009.06.002 ( reposiTUm)

Fleischner, H., Mujuni, E., Paulusma, D., & Szeider, S. (2009). Covering graphs with few complete bipartite subgraphs. Theoretical Computer Science, 410(21–23), 2045–2053. https://doi.org/10.1016/j.tcs.2008.12.059 ( reposiTUm)

Szeider, S. (2025). Large and Parallel Human Sorting Networks. In Creative Mathematical Sciences Communication : 7th International Conference, CMSC 2024, Trier, Germany, October 7–10, 2024, Proceedings (pp. 194–204). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73257-7_16 ( reposiTUm)

Ganian, R., Korchemna, V., & Szeider, S. (2024). Revisiting Causal Discovery from a Complexity-Theoretic Perspective. In K. Larson (Ed.), Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (pp. 3377–3385). International Joint Conferences on Artificial Intelligence. ( reposiTUm)

Xia, H., & Szeider, S. (2024). SAT-Based Tree Decomposition with Iterative Cascading Policy Selection. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24) (pp. 8191–8199). AAAI Press. https://doi.org/10.1609/aaai.v38i8.28659 ( reposiTUm)

Schidler, A., & Szeider, S. (2024). Structure-Guided Local Improvement for Maximum Satisfiability. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024) (pp. 26:1-26:23). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CP.2024.26 ( reposiTUm)

Reichl, F. X., Slivovsky, F., & Szeider, S. (2024). eSLIM: Circuit Minimization with SAT Based Local Improvement. In 27th International Conference on Theory and Applications of Satisfiability Testing (pp. 23:1-23:14). Schloss Dagstuhl. https://doi.org/10.4230/LIPIcs.SAT.2024.23 ( reposiTUm)

Kirchweger, M., & Szeider, S. (2024). Computing Small Rainbow Cycle Numbers with SAT Modulo Symmetries. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024) (pp. 37:1-37:11). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CP.2024.37 ( reposiTUm)

de Colnet, A., Szeider, S., & Zhang, T. (2024). Compilation and Fast Model Counting beyond CNF. In K. Larson (Ed.), Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (pp. 3315–3323). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2024/367 ( reposiTUm)

Chew, L., de Colnet, A., & Szeider, S. (2024). ASP-QRAT: A Conditionally Optimal Dual Proof System for ASP. In P. Marquis, M. Ortiz, & M. Pagnucco (Eds.), Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning (pp. 253–263). https://doi.org/10.24963/kr.2024/24 ( reposiTUm)

Ordyniak, S., Paesani, G., Rychlicki, M., & Szeider, S. (2024). Explaining Decisions in ML Models: A Parameterized Complexity Analysis. In Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning (pp. 563–573). IJCAI Organization. https://doi.org/10.24963/kr.2024/53 ( reposiTUm)

Dabrowski, K., Eiben, E., Ordyniak, S., Paesani, G., & Szeider, S. (2024). Learning Small Decision Trees for Data of Low Rank-Width. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024) (pp. 10476–10483). AAAI Press. https://doi.org/10.1609/aaai.v38i9.28916 ( reposiTUm)

Ordyniak, S., Paesani, G., Rychlicki, M., & Szeider, S. (2024). A General Theoretical Framework for Learning Smallest Interpretable Models. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (pp. 10662–10669). AAAI Press. https://doi.org/10.1609/aaai.v38i9.28937 ( reposiTUm)

Chew, L., De Colnet, A., Slivovsky, F., & Szeider, S. (2024). Hardness of Random Reordered Encodings of Parity for Resolution and CDCL. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI ’24) (pp. 7978–7986). AAAI Press. https://doi.org/10.1609/aaai.v38i8.28635 ( reposiTUm)

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)

Kirchweger, M., Peitl, T., & Szeider, S. (2023). Co-Certificate Learning with SAT Modulo Symmetries. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 1944–1953). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/216 ( reposiTUm)

Reichl, F.-X., Slivovsky, F., & Szeider, S. (2023). Circuit Minimization with QBF-Based Exact Synthesis. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (pp. 4087–4094). AAAI Press. https://doi.org/10.1609/aaai.v37i4.25524 ( reposiTUm)

Reichl, F. X., Slivovsky, F., & Szeider, S. (2023). Circuit Minimization with Exact Synthesis: From QBF Back to SAT. In IWLS 2023: 32nd International Workshop on Logic & Synthesis (pp. 98–105). ( reposiTUm)

Kirchweger, M., Peitl, T., & Szeider, S. (2023). A SAT Solver’s Opinion on the Erdos-Faber-Lovász Conjecture. In M. Mahajan (Ed.), 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023) (pp. 1–17). Schloss-Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SAT.2023.13 ( reposiTUm)

Eiben, E., Ordyniak, S., Paesani, G., & Szeider, S. (2023). Learning Small Decision Trees with Large Domain. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3184–3192). https://doi.org/10.24963/ijcai.2023/355 ( reposiTUm)

Ordyniak, S., Paesani, G., & Szeider, S. (2023). The Parameterized Complexity of Finding Concise Local Explanations. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3312–3320). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/369 ( reposiTUm)

Eiben, E., Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2023). From Data Completion to Problems on Hypercubes: A Parameterized Analysis of the Independent Set Problem. In N. Misra & M. Wahlström (Eds.), 18th International Symposium on Parameterized and Exact Computation (IPEC 2023) (pp. 1–14). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.IPEC.2023.16 ( reposiTUm)

Zhang, T., & Szeider, S. (2023). Searching for Smallest Universal Graphs and Tournaments with SAT. In R. Yap (Ed.), 29th International Conference on Principles and Practice of Constraint Programming. https://doi.org/10.4230/LIPIcs.CP.2023.39 ( 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)

Eiben, E., Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2023). The Computational Complexity of Concise Hypersphere Classification. In A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato, & J. Scarlett (Eds.), Proceedings of the 40th International Conference on Machine Learning (pp. 9060–9070). http://hdl.handle.net/20.500.12708/188983 ( reposiTUm)

Fazekas, K., Niemetz, A., Preiner, M., Kirchweger, M., Szeider, S., & Biere, A. (2023). IPASIR-UP: User Propagators for CDCL. In M. Mahajan & F. Slivovsky (Eds.), 26th International Conference on Theory and Applications of Satisfiability Testing (pp. 8:1-8:13). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SAT.2023.8 ( reposiTUm)

Markus Kirchweger, Scheucher, M., & Szeider, S. (2023). SAT-Based Generation of Planar Graphs. In 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023). 26th International Conference on Theory and Applications of Satisfiability Testing (SAT), Alghero, Italy. Schloss-Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SAT.2023.14 ( reposiTUm)

Peruvemba Ramaswamy, V., & Szeider, S. (2022). Learning Fast-Inference Bayesian Networks. In Advances in Neural Information Processing Systems 34 (NeurIPS 2021). 35th conference on neural information processing systems (NeurIPS 2021), Unknown. https://doi.org/10.34726/4023 ( reposiTUm)

Schidler, A., & Szeider, S. (2022). A SAT Approach to Twin-Width. In 2022 Proceedings of the Symposium on Algorithm Engineering and Experiments (ALENEX) (pp. 67–77). https://doi.org/10.1137/1.9781611977042.6 ( reposiTUm)

Dvořák, W., Hecher, M., König, M., Schidler, A., Szeider, S., & Woltran, S. (2022). Tractable Abstract Argumentation via Backdoor-Treewidth. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (pp. 5608–5615). AAAI Press. https://doi.org/10.1609/aaai.v36i5.20501 ( reposiTUm)

Peruvemba Ramaswamy, V., & Szeider, S. (2022). Learning Large Bayesian Networks with Expert Constraints. In Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) (pp. 1592–1601). PMLR. https://doi.org/10.34726/3821 ( reposiTUm)

Dreier, J., Ordyniak, S., & Szeider, S. (2022). SAT Backdoors: Depth Beats Size. In 30th Annual European Symposium on Algorithms (ESA 2022) (pp. 1–18). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ESA.2022.46 ( reposiTUm)

Dreier, J., Ordyniak, S., & Szeider, S. (2022). CSP Beyond Tractable Constraint Languages. In C. Solnon (Ed.), 28th International Conference on Principles and Practice of Constraint Programming (pp. 1–17). Schloss Dagstuhl, Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CP.2022.20 ( reposiTUm)

Eiben, E., Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2022). Finding a Cluster in Incomplete Data. In 30th Annual European Symposium on Algorithms (ESA 2022) (pp. 1–14). Schloss Dagstuhl -- Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ESA.2022.47 ( reposiTUm)

Ganian, R., Pokrývka, F., Schidler, A., Simonov, K., & Szeider, S. (2022). Weighted Model Counting with Twin-Width. In K. S. Meel & O. Strichman (Eds.), 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022) (pp. 1–17). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SAT.2022.15 ( reposiTUm)

Kirchweger, M., Scheucher, M., & Szeider, S. (2022). A SAT Attack on Rota’s Basis Conjecture. In 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022) (pp. 1–18). Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH. https://doi.org/10.4230/LIPIcs.SAT.2022.4 ( reposiTUm)

Ramaswamy, V. P., & Szeider, S. (2021). Turbocharging Treewidth-Bounded Bayesian Network Structure Learning. In Thirty-Fifth AAAI Conference on Artificial Intelligence (pp. 3895–3903). AAAI Press. http://hdl.handle.net/20.500.12708/58598 ( reposiTUm)

Ordyniak, S., & Szeider, S. (2021). Parameterized Complexity of Small Decision Tree Learning. In Thirty-Fifth AAAI Conference on Artificial Intelligence (pp. 1–9). AAAI Press. http://hdl.handle.net/20.500.12708/58602 ( reposiTUm)

Kirchweger, M., & Szeider, S. (2021). SAT Modulo Symmetries for Graph Generation. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021) (pp. 1–16). LIPICS. https://doi.org/10.4230/LIPIcs.CP.2021.34 ( reposiTUm)

Eiben, E., Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2021). The Parameterized Complexity of Clustering Incomplete Data. In Thirty-Fifth AAAI Conference on Artificial Intelligence (pp. 7296–7304). AAAI Press. http://hdl.handle.net/20.500.12708/58587 ( reposiTUm)

Reichl, F.-X., Slivovsky, F., & Szeider, S. (2021). Certified DQBF Solving by Definition Extraction. In Theory and Applications of Satisfiability Testing – SAT 2021 (pp. 499–517). LNCS / Springer. https://doi.org/10.1007/978-3-030-80223-3_34 ( reposiTUm)

Ganian, R., Schidler, A., Sorge, M., & Szeider, S. (2021). Threshold Treewidth and Hypertree Width. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. IJCAI’20: Twenty-Ninth International Joint Conference on Artificial Intelligence, Yokohama, Japan. https://doi.org/10.24963/ijcai.2020/263 ( reposiTUm)

Schidler, A., & Szeider, S. (2021). Computing Optimal Hypertree Decompositions with SAT. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence, Montreal, Canada, Canada. https://doi.org/10.24963/ijcai.2021/196 ( reposiTUm)

Schidler, A., & Szeider, S. (2021). SAT-based Decision Tree Learning for Large Data Sets. In Thirty-Fifth AAAI Conference on Artificial Intelligence (pp. 3904–3912). AAAI Press. http://hdl.handle.net/20.500.12708/58603 ( reposiTUm)

Peitl, T., & Szeider, S. (2021). Finding the Hardest Formulas for Resolution (Extended Abstract). In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence, Montreal, Canada, Canada. https://doi.org/10.24963/ijcai.2021/657 ( reposiTUm)

Fichte, J. K., Hecher, M., & Szeider, S. (2020). A Time Leap Challenge for SAT-Solving. In Principles and Practice of Constraint Programming 26th International Conference, CP 2020, Louvain-la-Neuve, Belgium, September 7–11, 2020, Proceedings (pp. 267–285). https://doi.org/10.1007/978-3-030-58475-7_16 ( reposiTUm)

Fichte, J. K., Hecher, M., & Szeider, S. (2020). Breaking Symmetries with RootClique and LexTopSort. In Principles and Practice of Constraint Programming 26th International Conference, CP 2020, Louvain-la-Neuve, Belgium, September 7–11, 2020, Proceedings (pp. 286–303). https://doi.org/10.1007/978-3-030-58475-7_17 ( reposiTUm)

Shukla, A., Slivovsky, F., & Szeider, S. (2020). Short Q-Resolution Proofs with Homomorphisms. In Theory and Applications of Satisfiability Testing – SAT 2020 (pp. 412–428). LNCS. https://doi.org/10.1007/978-3-030-51825-7_29 ( reposiTUm)

Peruvemba Ramaswamy, V., & Szeider, S. (2020). MaxSAT-Based Postprocessing for Treedepth. In Principles and Practice of Constraint Programming 26th International Conference, CP 2020, Louvain-la-Neuve, Belgium, September 7–11, 2020, Proceedings (pp. 478–495). LNCS. https://doi.org/10.1007/978-3-030-58475-7_28 ( reposiTUm)

Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2020). On the Parameterized Complexity of Clustering Incomplete Data into Subspaces of Small Rank. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 3906–3913). AAAI Press. https://doi.org/10.1609/aaai.v34i04.5804 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2020). A Faster Algorithm for Propositional Model Counting Parameterized by Incidence Treewidth. In Theory and Applications of Satisfiability Testing – SAT 2020 (pp. 267–276). LNCS. https://doi.org/10.1007/978-3-030-51825-7_19 ( reposiTUm)

Kovács, L., Lachnitt, H., & Szeider, S. (2020). Formalizing Graph Trail Properties in Isabelle/HOL. In Intelligent Computer Mathematics 13th International Conference, CICM 2020, Bertinoro, Italy, July 26–31, 2020, Proceedings (pp. 190–205). LNCS. https://doi.org/10.1007/978-3-030-53518-6_12 ( reposiTUm)

Schidler, A., & Szeider, S. (2020). Computing Optimal Hypertree Decompositions. In 2020 Proceedings of the Twenty-Second Workshop on Algorithm Engineering and Experiments (ALENEX) (pp. 1–11). siam. https://doi.org/10.1137/1.9781611976007.1 ( reposiTUm)

Ganian, R., Peitl, T., Slivovsky, F., & Szeider, S. (2020). Fixed-Parameter Tractability of Dependency QBF with Structural Parameters. In Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning. 17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020, Rhodes, Greece. https://doi.org/10.24963/kr.2020/40 ( reposiTUm)

Peitl, T., & Szeider, S. (2020). Finding the Hardest Formulas for Resolution. In Principles and Practice of Constraint Programming 26th International Conference, CP 2020, Louvain-la-Neuve, Belgium, September 7–11, 2020, Proceedings (pp. 514–530). LNCS. https://doi.org/10.1007/978-3-030-58475-7_30 ( reposiTUm)

Ganian, R., Lodha, N., Ordyniak, S., & Szeider, S. (2019). SAT-Encodings for Treecut Width and Treedepth. In S. G. Kobourov & H. Meyerhenke (Eds.), Proceedings of the Twenty-First Workshop on Algorithm Engineering and Experiments (ALENEX). SIAM. https://doi.org/10.1137/1.9781611975499 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2019). Proof Complexity of Fragments of Long-Distance Q-Resolution. In Theory and Applications of Satisfiability Testing – SAT 2019 (pp. 319–335). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-24258-9_23 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2019). Combining Resolution-Path Dependencies with Dependency Learning. In Theory and Applications of Satisfiability Testing – SAT 2019 22nd International Conference, SAT 2019, Lisbon, Portugal, July 9–12, 2019, Proceedings. Int. Conference on Theory and Applications of Satisfiability Testing, Trento, Italy. LNCS. https://doi.org/10.1007/978-3-030-24258-9_22 ( reposiTUm)

Fichte, J., Hecher, M., Lodha, N., & Szeider, S. (2018). An SMT Approach to Fractional Hypertree Width. In J. Hooker (Ed.), Principles and Practice of Constraint Programming, 24th International Conference, CP 2018 (pp. 109–127). Springer-Verlag. https://doi.org/10.1007/978-3-319-98334-9_8 ( reposiTUm)

Hoos, H. H., Peitl, T., Slivovsky, F., & Szeider, S. (2018). Portfolio-Based Algorithm Selection for Circuit QBFs. In Principles and Practice of Constraint Programming 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings (pp. 195–209). Springer-Verlag. https://doi.org/10.1007/978-3-319-98334-9_13 ( reposiTUm)

Ganian, R., Kanj, I., Ordyniak, S., & Szeider, S. (2018). Parameterized Algorithms for the Matrix Completion Problem. In Proceeding of ICML (pp. 1642–1651). Journal of Machine Learning Research. http://hdl.handle.net/20.500.12708/57440 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2018). Polynomial-Time Validation of QCDCL Certificates. In O. Beyersdorff & C. M. Wintersteiger (Eds.), Theory and Applications of Satisfiability Testing – SAT 2018 (pp. 253–269). Springer-Verlag, Lecture Notes in Artificial Intelligence 8268. https://doi.org/10.1007/978-3-319-94144-8_16 ( reposiTUm)

Ganian, R., Ramanujan, M. S., & Szeider, S. (2017). Combining Treewidth and Backdoors for CSP. In H. Vollmer & B. Vallée (Eds.), 34th Symposium on Theoretical Aspects of Computer Science (pp. 429–445). Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany. https://doi.org/10.4230/LIPIcs.STACS.2017.36 ( reposiTUm)

Lodha, N., Ordyniak, S., & Szeider, S. (2017). SAT-Encodings for Special Treewidth and Pathwidth. In Theory and Applications of Satisfiability Testing – SAT 2017 (pp. 429–445). Springer International Publishing AG 2017. https://doi.org/10.1007/978-3-319-66263-3_27 ( reposiTUm)

Ganian, R., Ramanujan, M. S., & Szeider, S. (2017). Backdoor Treewidth for SAT. In Theory and Applications of Satisfiability Testing – SAT 2017 (pp. 20–37). Springer-Verlag. https://doi.org/10.1007/978-3-319-66263-3_2 ( reposiTUm)

Ganian, R., & Szeider, S. (2017). New Width Parameters for Model Counting. In Theory and Applications of Satisfiability Testing – SAT 2017 (pp. 38–52). International Conference on Theory and Applications of Satisfiability Testing. https://doi.org/10.1007/978-3-319-66263-3_3 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2017). Dependency Learning for QBF. In S. Gaspers & T. Walsh (Eds.), Theory and Applications of Satisfiability Testing – SAT 2017 : 20th International Conference, Melbourne, VIC, Australia, August 28 – September 1, 2017, Proceedings. Cham. https://doi.org/10.1007/978-3-319-66263-3_19 ( reposiTUm)

Fichte, J., & Szeider, S. (2017). Backdoor Trees for Answer Set Programming. In B. Bogaerts & A. Harrison (Eds.), Proceedings of the 10th Workshop on Answer Set Programming and Other Computing Paradigms co-located with the 14th International Conference on Logic Programming and Nonmonotonic Reasoning (ASPOCP@LPNMR’17 (pp. 1–16). http://hdl.handle.net/20.500.12708/55469 ( reposiTUm)

Fichte, J. K., Lodha, N., & Szeider, S. (2017). SAT-Based Local Improvement for Finding Tree Decompositions of Small Width. In S. Gaspers & T. Walsh (Eds.), Theory and Applications of Satisfiability Testing – SAT 2017 (pp. 401–411). Lecture Notes in Computer Science (LNCS) / Springer. https://doi.org/10.1007/978-3-319-66263-3_25 ( reposiTUm)

Ramanujan, M. S., & Szeider, S. (2017). Rigging Nearly Acyclic Tournaments Is Fixed-Parameter Tractable. In Thirty-First AAAI Conference on Artificial Intelligence (pp. 3929–3935). http://hdl.handle.net/20.500.12708/57271 ( reposiTUm)

Lodha, N., Ordyniak, S., & Szeider, S. (2017). A SAT Approach to Branchwidth. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017) (pp. 4894–4898). http://hdl.handle.net/20.500.12708/57272 ( reposiTUm)

Peitl, T., Slivovsky, F., & Szeider, S. (2016). Long Distance Q-Resolution with Dependency Schemes. In N. Creignou & D. Le Berre (Eds.), Theory and Applications of Satisfiability Testing – SAT 2016 : 19th International Conference, Bordeaux, France, July 5-8, 2016, Proceedings (pp. 500–518). Cham. https://doi.org/10.1007/978-3-319-40970-2_31 ( reposiTUm)

Ganian, R., Ramanujan, M. S., & Szeider, S. (2016). Backdoors to Tractable Valued CSP. In Principles and Practice of Constraint Programming (Proceedings of 22nd CP) (pp. 233–250). LNCS. http://hdl.handle.net/20.500.12708/56665 ( reposiTUm)

Ganian, R., Kalany, M., Szeider, S., & Träff, J. L. (2016). Polynomial-Time Construction of Optimal MPI Derived Datatype Trees. In 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS). IEEE 30th International Parallel and Distributed Processing Symposium (IPDPS 2016), Chicago, United States of America (the). IEEE Computer Society. https://doi.org/10.1109/ipdps.2016.13 ( reposiTUm)

de Haan, R., & Szeider, S. (2016). Parameterized Complexity Results for Symbolic Model Checking of Temporal Logics. In Proceedings of the 15th International Conference on Principles of Knowledge Representation and Reasoning - KR 2016 (pp. 453–462). http://hdl.handle.net/20.500.12708/56825 ( reposiTUm)

Lodha, N., Ordyniak, S., & Szeider, S. (2016). A SAT Approach to Branchwidth. In Proceedings of SAT 2016: Theory and Applications of Satisfiability Testing - SAT 2016 (pp. 179–195). http://hdl.handle.net/20.500.12708/56670 ( reposiTUm)

Ganian, R., de Haan, R., Kanj, I., & Szeider, S. (2016). On Existential MSO and its Relation to ETH. In Proceedings of the 41st International Symposium on Mathematical Foundations of Computer Science (pp. 1–14). http://hdl.handle.net/20.500.12708/56669 ( reposiTUm)

Ganian, R., Ramanujan, M. S., & Szeider, S. (2016). Discovering Archipelagos of Tractability for Constraint Satisfaction and Counting. In R. Krauthgamer (Ed.), Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1670–1681). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611974331.ch114 ( reposiTUm)

de Haan, R., Endriss, U., & Szeider, S. (2015). Parameterized Complexity Results for Agenda Safety in Judgment Aggregation. In G. Weiss, P. Yolum, R. H. Bordini, & E. Elkind (Eds.), Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems - AAMAS 2015 (pp. 127–136). http://hdl.handle.net/20.500.12708/56187 ( reposiTUm)

Ganian, R., & Szeider, S. (2015). Community Structure Inspired Algorithms for SAT and #SAT. In Proceedings of the 18th International Conference on Theory and Applications of Satisfiability Testing (pp. 223–238). LNCS / Springer. http://hdl.handle.net/20.500.12708/56452 ( reposiTUm)

Eiben, E., Ganian, R., & Szeider, S. (2015). Solving Problems on Graphs of High Rank-Width. In Proceedings of the 14th International Symposium on Algorithms and Data Structures (pp. 314–326). LNCS. http://hdl.handle.net/20.500.12708/56453 ( reposiTUm)

Eiben, E., Ganian, R., & Szeider, S. (2015). Meta-kernelization using Well-structured Modulators. In T. Husfeldt & I. Kanj (Eds.), 10th International Symposium on Parameterized and Exact Computation (IPEC 2015) (pp. 114–126). LIPICs. https://doi.org/10.4230/LIPIcs.IPEC.2015.114 ( reposiTUm)

de Haan, R., & Szeider, S. (2015). Machine Characterizations for Parameterized Complexity Classes Beyond Para-NP. In G. F. Italiano, T. Margaria, J. Pokorný, J.-J. Quisquater, & R. Wattenhofer (Eds.), SOFSEM 2015: Theory and Practice of Computer Science 41st International Conference on Current Trends in Theory and Practice of Computer Science, Pec pod Sněžkou, Czech Republic, January 24-29, 2015, Proceedings. LNCS. https://doi.org/10.1007/978-3-662-46078-8_18 ( reposiTUm)

Ganian, R., Kim, E. J., & Szeider, S. (2015). Algorithmic Applications of Tree-Cut Width. In Proceedings of the 40th International Symposium Mathematical Foundations of Computer Science 2015 (pp. 348–361). http://hdl.handle.net/20.500.12708/56451 ( reposiTUm)

Bova, S., Ganian, R., & Szeider, S. (2014). Model Checking Existential Logic on Partially Ordered Sets. In CSL-LICS 2014. Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), Vienna, Austria. ACM New York, NY, USA. http://hdl.handle.net/20.500.12708/55811 ( reposiTUm)

Endriss, U., de Haan, R., & Szeider, S. (2014). Parameterized Complexity Results for Agenda Safety in Judgment Aggregation. In COMSOC 2014. International Workshop on Computational Social Choice (COMSOC), Krakow, Poland. http://hdl.handle.net/20.500.12708/55806 ( reposiTUm)

Kanj, I., de Haan, R., & Szeider, S. (2014). Subexponential Time Complexity of CSP with Global Constraints. In CP 2014 (pp. 272–288). LNCS / Springer. http://hdl.handle.net/20.500.12708/55810 ( reposiTUm)

Gaspers, S., Misra, N., Ordyniak, S., Szeider, S., & Zivný, S. (2014). Backdoors into Heterogeneous Classes of SAT and CSP. In AAAI 2014 (pp. 2652–2658). http://hdl.handle.net/20.500.12708/55809 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2014). Dependency Schemes and Q-resolution. In SAT 2014 (pp. 269–284). LNCS / Springer. http://hdl.handle.net/20.500.12708/55816 ( reposiTUm)

Kim, E. J., Ordyniak, S., & Szeider, S. (2014). The Complexity of Repairing, Adjusting, and Aggregating of Extensions in Abstract Argumentation. In TAFA 2013 (pp. 158–175). LNAI / Springer. http://hdl.handle.net/20.500.12708/55815 ( reposiTUm)

Bova, S., Ganian, R., & Szeider, S. (2014). Quantified Conjunctive Queries on Partially Ordered Sets. In IPEC 2014 (pp. 122–134). LNCS / Springer. http://hdl.handle.net/20.500.12708/55812 ( reposiTUm)

de Haan, R., & Szeider, S. (2014). Fixed-Parameter Tractable Reductions to SAT. In SAT 2014 (pp. 85–102). LNCS / Springer. http://hdl.handle.net/20.500.12708/55808 ( reposiTUm)

de Haan, R., & Szeider, S. (2014). The Parameterized Complexity of Reasoning Problems Beyond NP. In KR 2014 (pp. 82–91). http://hdl.handle.net/20.500.12708/55807 ( reposiTUm)

Kanj, I., de Haan, R., & Szeider, S. (2014). Small Unsatisfiable Subsets in Constraint Satisfaction. In IEEE-ICTAI 2014. The IEEE International Conference on Tools with Artificial Intelligence, Special Track on SAT and CSP Technologies (ICTAI), Washington D.C., United States of America (the). http://hdl.handle.net/20.500.12708/55734 ( reposiTUm)

Gaspers, S., Ordyniak, S., Ramanujan, M. S., Saurabh, S., & Szeider, S. (2013). Backdoors to q-Horn. In N. Portier & T. Wilke (Eds.), 30th Symposium on Theoretical Aspects of Computer Science (STACS´13) (pp. 67–79). Dagstuhl Publishing. http://hdl.handle.net/20.500.12708/54875 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2013). Model Counting for Formulas of Bounded Clique-Width. In L. Cai, S.-W. Cheng, & T.-W. Lam (Eds.), Algorithms and Computation (pp. 677–687). Springer / LNCS. https://doi.org/10.1007/978-3-642-45030-3_63 ( reposiTUm)

Gaspers, S., & Szeider, S. (2013). Strong Backdoors to Bounded Treewidth SAT. In O. Reingold (Ed.), 2013 IEEE 54th Annual Symposium on Foundations of Computer Science. IEEE. https://doi.org/10.1109/focs.2013.59 ( reposiTUm)

Ganian, R., Slivovsky, F., & Szeider, S. (2013). Meta-kernelization with Structural Parameters. In K. Chatterjee & J. Sgall (Eds.), Mathematical Foundations of Computer Science 2013 (pp. 457–468). Springer / LNCS. https://doi.org/10.1007/978-3-642-40313-2_41 ( reposiTUm)

Paulusma, D., Slivovsky, F., & Szeider, S. (2013). Model Counting for CNF Formulas of Bounded Modular Treewidth. In N. Portier & T. Wilke (Eds.), 30th Symposium on Theoretical Aspects of Computer Science (STACS´13) (pp. 55–66). Dagstuhl Publishing. http://hdl.handle.net/20.500.12708/54874 ( reposiTUm)

Szeider, S. (2013). Capturing Structure in Hard Combinatorial Problems. In Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI). The IEEE International Conference on Tools with Artificial Intelligence, Special Track on SAT and CSP Technologies (ICTAI), Washington D.C., USA, Non-EU. http://hdl.handle.net/20.500.12708/54879 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2013). Variable Dependencies and Q-Resolution. In F. Lonsing & M. Seidl (Eds.), International Workshop on Quantified Boolean Formulas 2013 Informal Workshop Report (pp. 22–29). http://hdl.handle.net/20.500.12708/54888 ( reposiTUm)

Müller, M., & Szeider, S. (2013). Revisiting Space in Proof Complexity: Treewidth and Pathwidth. In K. Chatterjee & J. Sgall (Eds.), Mathematical Foundations of Computer Science 2013 (pp. 704–716). Springer / LNCS. https://doi.org/10.1007/978-3-642-40313-2_62 ( reposiTUm)

Bäckström, C., Jonsson, P., Ordyniak, S., & Szeider, S. (2013). Parameterized Complexity and Kernel Bounds for Hard Planning Problems. In P. G. Spirakis & M. Serna (Eds.), Algorithms and Complexity 8th International Conference, CIAC 2013, Barcelona, Spain, May 22-24, 2013. Proceedings. Springer / LNCS. https://doi.org/10.1007/978-3-642-38233-8_2 ( reposiTUm)

Szeider, S. (2013). The Parameterized Complexity of Constraint Satisfaction and Reasoning. In H. Tompits, S. Abreu, J. Oetsch, J. Pührer, D. Seipel, M. Umeda, & A. Wolf (Eds.), Applications of Declarative Programming and Knowledge Management (pp. 27–37). Springer / LNCS. https://doi.org/10.1007/978-3-642-41524-1_2 ( reposiTUm)

Bliem, B., Pichler, R., & Woltran, S. (2013). Declarative Dynamic Programming as an Alternative Realization of Courcelle’s Theorem. In G. Gutin & S. Szeider (Eds.), Parameterized and Exact Computation (pp. 28–40). Springer. https://doi.org/10.1007/978-3-319-03898-8_4 ( reposiTUm)

de Haan, R., Kanj, I., & Szeider, S. (2013). Local Backbones. In M. Järvisalo & A. Van Gelder (Eds.), Theory and Applications of Satisfiability Testing - SAT 2013 16th International Conference, Helsinki, Finland, July 8-12, 2013, Proceedings. LNCS / Springer. https://doi.org/10.1007/978-3-642-39071-5_28 ( reposiTUm)

Misra, N., Ordyniak, S., Raman, V., & Szeider, S. (2013). Upper and Lower Bounds for Weak Backdoor Set Detection. In M. Järvisalo & A. Van Gelder (Eds.), Theory and Applications of Satisfiability Testing - SAT 2013 16th International Conference, Helsinki, Finland, July 8-12, 2013, Proceedings. Springer / LNCS. https://doi.org/10.1007/978-3-642-39071-5_29 ( reposiTUm)

Heule, M., & Szeider, S. (2013). A SAT Approach to Clique-Width. In M. Järvisalo & A. Van Gelder (Eds.), Theory and Applications of Satisfiability Testing - SAT 2013 16th International Conference, Helsinki, Finland, July 8-12, 2013, Proceedings. Springer / LNCS. https://doi.org/10.1007/978-3-642-39071-5_24 ( reposiTUm)

Kanj, I., & Szeider, S. (2013). On the Subexponential Time Complexity of CSP. In M. desJardins & M. Littman (Eds.), Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI´13) (pp. 459–465). AAAI Press. http://hdl.handle.net/20.500.12708/54867 ( reposiTUm)

de Haan, R., Roubickova, A., & Szeider, S. (2013). Parameterized Complexity Results for Plan Reuse. In M. desJardins & M. Littman (Eds.), Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI´13) (pp. 224–231). AAAI Press. http://hdl.handle.net/20.500.12708/54863 ( reposiTUm)

Fichte, J., & Szeider, S. (2013). Backdoors to Normality for Disjunctive Logic Programs. In M. desJardins & M. Littman (Eds.), Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI´13) (pp. 320–327). AAAI Press. http://hdl.handle.net/20.500.12708/54865 ( reposiTUm)

Pfandler, A., Rümmele, S., & Szeider, S. (2013). Backdoors to Abduction. In F. Rossi (Ed.), Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (pp. 1046–1052). AAAI Press. http://hdl.handle.net/20.500.12708/54790 ( reposiTUm)

Slivovsky, F., & Szeider, S. (2012). Computing Resolution-Path Dependencies in Linear Time ,. In A. Cimatti & R. Sebastiani (Eds.), Theory and Applications of Satisfiability Testing – SAT 2012 (pp. 58–71). LNCS / Springer. https://doi.org/10.1007/978-3-642-31612-8_6 ( reposiTUm)

Gaspers, S., & Szeider, S. (2012). Strong Backdoors to Nested Satisfiability. In A. Cimatti & R. Sebastiani (Eds.), Proceedings of the Fifteen International Conference on Theory and Applications of Satisfiability Testing (SAT 2012) (pp. 58–71). LNCS / Springer. http://hdl.handle.net/20.500.12708/54319 ( reposiTUm)

Fomin, F. V., Gaspers, S., Golovach, P., Suchan, K., Szeider, S., van Leeuwen, E. J., Vatshelle, M., & Villanger, Y. (2012). k-Gap Interval Graphs. In D. Fernández-Baca (Ed.), LATIN 2012: Theoretical Informatics (pp. 350–361). Lecture Notes in Computer Science / Springer. https://doi.org/10.1007/978-3-642-29344-3_30 ( reposiTUm)

Gaspers, S., Kim, E. J., Ordyniak, S., Saurabh, S., & Szeider, S. (2012). Don’t Be Strict in Local Search! In J. Hoffmann & B. Selman (Eds.), Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012) (pp. 486–492). AAAI Press. http://hdl.handle.net/20.500.12708/54316 ( reposiTUm)

Gaspers, S., Koivisto, M., Liedloff, M., Ordyniak, S., & Szeider, S. (2012). On Finding Optimal Polytrees. In J. Hoffmann & B. Selman (Eds.), Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012) (pp. 750–756). AAAI Press. http://hdl.handle.net/20.500.12708/54315 ( reposiTUm)

Gaspers, S., & Szeider, S. (2012). Backdoors to Acyclic SAT. In Automata, Languages, and Programming (pp. 363–374). Springer-Verlag. https://doi.org/10.1007/978-3-642-31594-7_31 ( reposiTUm)

Fichte, J., & Szeider, S. (2012). Backdoors to Normality for Disjunctive Logic Programs. In Y. Lierler & M. Fink (Eds.), Proceedings of the 5th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP 2012) (pp. 99–113). http://hdl.handle.net/20.500.12708/54323 ( reposiTUm)

Bäckström, C., Chen, Y., Jonsson, P., Ordyniak, S., & Szeider, S. (2012). The Complexity of Planning Revisited - A Parameterized Analysis. In J. Hoffmann & B. Selman (Eds.), Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012) (pp. 1735–1741). AAAI Press. http://hdl.handle.net/20.500.12708/54314 ( reposiTUm)

Dvorak, W., & Spanring, C. (2012). Comparing the Expressiveness of Argumentation Semantics. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Proceedings of Computational Models of Argument - Proceedings of COMMA 2012 (pp. 261–272). Frontiers in Artificial Intelligence and Applications / IOS Press. http://hdl.handle.net/20.500.12708/54496 ( reposiTUm)

Dvorak, W., & Gaggl, S. (2012). Computational Aspects of cf2 and stage2 Argumentation Semantics. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Proceedings of Fourth International Conference on Computational Models of Argument (pp. 273–284). “Frontiers in Artificial Intelligence and Applications” series/IOS Press. http://hdl.handle.net/20.500.12708/54177 ( reposiTUm)

Ellmauthaler, S., & Wallner, J. P. (2012). Evaluating Abstract Dialectical Frameworks with ASP. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Proceedings of Computational Models of Argument - Proceedings of COMMA 2012 (pp. 505–506). IOS Press. http://hdl.handle.net/20.500.12708/54186 ( reposiTUm)

Egly, U., Creignou, N., & Schmidt, J. (2012). Complexity of logic-based argumentation in Schaefer’s framework. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Computational Models of Argument (pp. 237–248). IOS Press. http://hdl.handle.net/20.500.12708/54461 ( reposiTUm)

Charwat, G., & Dvorak, W. (2012). dynPARTIX 2.0 - Dynamic Programming Argumentation Reasoning Tool. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Proceedings of Computational Models of Argument - Proceedings of COMMA 2012 (pp. 507–508). Frontiers in Artificial Intelligence and Applications / IOS Press. http://hdl.handle.net/20.500.12708/54497 ( reposiTUm)

Kim, E. J., & Ordyniak, S. (2012). Valued-Based Argumentation for Tree-like Value Graphs. In B. Verheij, S. Szeider, & S. Woltran (Eds.), Fourth International Conference on Computational Models of Argument (Comma 2012) (pp. 378–389). IOS Press. http://hdl.handle.net/20.500.12708/54321 ( reposiTUm)

Dvořák, W., Szeider, S., & Woltran, S. (2012). Abstract Argumentation via Monadic Second Order Logic. In E. Hüllermeier, S. Link, T. Fober, & B. Seeger (Eds.), Scalable Uncertainty Management 6th International Conference, SUM 2012, Marburg, Germany, September 17-19, 2012, Proceedings (pp. 85–98). Lecture Notes in Computer Science / Springer. https://doi.org/10.1007/978-3-642-33362-0_7 ( reposiTUm)

Fichte, J., & Szeider, S. (2011). Backdoors to Tractable Answer-Set Programming. In T. Walsh (Ed.), Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (pp. 863–868). http://hdl.handle.net/20.500.12708/53762 ( reposiTUm)

Ordyniak, S., & Szeider, S. (2011). Augmenting Tractable Fragments of Abstract Argumentation. In T. Walsh (Ed.), Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (pp. 1033–1038). http://hdl.handle.net/20.500.12708/53761 ( reposiTUm)

Gaspers, S., & Szeider, S. (2011). Kernels for Global Constraints. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011) (pp. 540–545). http://hdl.handle.net/20.500.12708/53760 ( reposiTUm)

Szeider, S. (2011). Limits of Preprocessing. In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI 2011) (pp. 93–98). http://hdl.handle.net/20.500.12708/53759 ( reposiTUm)

Gaspers, S., & Szeider, S. (2011). The Parameterized Complexity of Local Consistency. In Principles and Practice of Constraint Programming – CP 2011 (pp. 302–316). Lecture Notes in Computer Science, Springer. https://doi.org/10.1007/978-3-642-23786-7_24 ( reposiTUm)

Ordyniak, S., Paulusma, D., & Szeider, S. (2011). Satisfiability of Acyclic and almost Acyclic CNF Formulas (II). In Theory and Applications of Satisfiability Testing - SAT 2011 (pp. 47–60). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-21581-0_6 ( reposiTUm)

Ordyniak, S., & Szeider, S. (2010). Algorithms and Complexity Results for Exact Bayesian Structure Learning. In P. Grünwald & P. Spirtes (Eds.), Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) (pp. 401–408). AUAI Press. http://hdl.handle.net/20.500.12708/53324 ( reposiTUm)

Van´t Hof, P., Kaminski, M., Paulusma, D., Szeider, S., & Thilikos, D. M. (2010). On Contracting Graphs to Fixed Pattern Graphs. In SOFSEM 2010: Theory and Practice of Computer Science (pp. 503–514). Springer. https://doi.org/10.1007/978-3-642-11266-9_42 ( reposiTUm)

Alon, N., Gutin, G., Kim, E. J., Szeider, S., & Yeo, A. (2010). Solving MAX-r-SAT Above a Tight Lower Bound. In M. Charikar (Ed.), Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 511–517). ACM-SIAM. http://hdl.handle.net/20.500.12708/53318 ( reposiTUm)

Gutin, G., Kim, E. J., Soleimanfallah, A., Szeider, S., & Yeo, A. (2010). Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming. In V. Raman & S. Saurabh (Eds.), Parameterized and Exact Computation (pp. 158–169). Springer. https://doi.org/10.1007/978-3-642-17493-3_16 ( reposiTUm)

Ordyniak, S., Paulusma, D., & Szeider, S. (2010). Satisfiability of Acyclic and Almost Acyclic CNF Formulas. In K. Lodaya & M. Mahajan (Eds.), IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2010) (pp. 84–95). Leibniz International Proceedings in Informatics (LIPIcs). https://doi.org/10.4230/LIPIcs.FSTTCS.2010.84 ( reposiTUm)

Dvorak, W., Szeider, S., & Woltran, S. (2010). Reasoning in Argumentation Frameworks of Bounded Clique-Width. In P. Baroni, F. Cerutti, M. Giacomin, & G. R. Simari (Eds.), Proceedings of COMMA 2010 (pp. 219–230). IOS Press. http://hdl.handle.net/20.500.12708/53323 ( reposiTUm)

Kim, E. J., Ordyniak, S., & Szeider, S. (2010). Algorithms and Complexity Results for Persuasive Argumentation. In P. Baroni, F. Cerutti, M. Giacomin, & G. R. Simari (Eds.), Proceedings of Third International Conference on Computational Models of Argument (COMMA 2010) (pp. 311–322). IOS Press. http://hdl.handle.net/20.500.12708/53322 ( reposiTUm)

Pichler, R., Rümmele, S., Szeider, S., & Woltran, S. (2010). Tractable Answer-Set Programming with Weight Constraints: Bounded Treewidth Is not Enough. In F. Lin, U. Sattler, & M. Truszczynski (Eds.), Proc. of KR 2010 (p. 10). AAAI Press. http://hdl.handle.net/20.500.12708/53171 ( reposiTUm)

Szeider, S. (2010). Not So Easy Problems For Tree Decomposable Graphs. In Selected and revised papers of ICDM 2008 (pp. 179–190). Ramanujan Mathematical Society (RMS). http://hdl.handle.net/20.500.12708/53531 ( reposiTUm)

Samer, M., & Szeider, S. (2006). Constraint Satisfaction with Bounded Treewidth Revisited. In Proceedings of the 12th International Conference on Principles and Practice of Constraint Programming (pp. 499–513). Springer-Verlag. http://hdl.handle.net/20.500.12708/51373 ( reposiTUm)

Ganian, R., Kratochvíl, J., & Szeider, S. (2022). Preface: Ninth workshop on graph classes, optimization, and Width Parameters, Vienna, Austria. In S. Szeider, R. Ganian, & J. Kratochwill (Eds.), Ninth workshop on graph classes, optimization, and Width Parameters (Vol. 312). https://doi.org/10.1016/j.dam.2022.02.009 ( reposiTUm)

Samer, M., & Szeider, S. (2021). Chapter 17. Fixed-Parameter Tractability. In A. Biere, M. Heule, H. van Maaren, & T. Walsh (Eds.), Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/faia201000 ( reposiTUm)

Szeider, S., Ordyniak, S., & Gaspers, S. (2017). The Constraint Satisfaction Problem: Complexity and Approximability. In The Constraint Satisfaction Problem: Complexity and Approximability (pp. 137–157). Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany. http://hdl.handle.net/20.500.12708/29616 ( reposiTUm)

Gaspers, S., & Szeider, S. (2012). Backdoors to Satisfaction. In H. L. Bodlaender, R. G. Downey, F. Fomin, & D. Marx (Eds.), The Multivariate Algorithmic Revolution and Beyond (pp. 287–317). Springer LNCS. https://doi.org/10.1007/978-3-642-30891-8_15 ( reposiTUm)

Modgil, S., Toni, F., Bex, F., Bratko, I., Chesñevar, C. I., Dvořák, W., Falappa, M. A., Fan, X., Gaggl, S. A., García, A. J., González, M. P., Gordon, T. F., Leite, J., Možina, M., Reed, C., Simari, G. R., Szeider, S., Torroni, P., & Woltran, S. (2012). The Added Value of Argumentation. In S. Ossowski (Ed.), Agreement Technologies (pp. 357–403). Springer Netherlands. https://doi.org/10.1007/978-94-007-5583-3_21 ( reposiTUm)

Theory and Applications of Satisfiability Testing – SAT 2010. (2010). In O. Strichman & S. Szeider (Eds.), Lecture Notes in Computer Science. Springer. https://doi.org/10.1007/978-3-642-14186-7 ( reposiTUm)

Szeider, S., Ganian, R., & Silva, A. (Eds.). (2022). 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022). https://doi.org/10.4230/LIPIcs.MFCS.2022.0 ( reposiTUm)

Gutin, G., & Szeider, S. (Eds.). (2013). Parameterized and Exact Computation, 8th International Symposium, IPEC 2013 (LNCS 8246). Springer-Verlag. http://hdl.handle.net/20.500.12708/23746 ( reposiTUm)

MFCS & CSL 2010 Satellite Workshops: Selected Papers, Fundamenta Informaticae 123. (2013). In A. Kucera, I. Potapov, A. Ciabattoni, S. Szeider, & R. Freivalds (Eds.), Fundamenta Informaticae. IOS Press. http://hdl.handle.net/20.500.12708/23747 ( reposiTUm)

Verheij, B., Szeider, S., & Woltran, S. (Eds.). (2012). Fourth International Conference on Computational Models of Argument (COMMA 2012). IOS Press. http://hdl.handle.net/20.500.12708/23575 ( reposiTUm)

Szeider, S. (2024, July 3). Circuit Minimization with QBF and SAT-Based Exact Synthesis [Presentation]. Synthesis of Models and Systems, California, United States of America (the). ( reposiTUm)

Szeider, S. (2024, October 10). Parameterized Complexity Problems in Explainable AI [Presentation]. Dagstuhl Seminar 24411 - New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition, Dagstuhl, Germany. ( reposiTUm)

Szeider, S. (2024, November 1). Neurosymbolic AI: Deep Learning and Deep Reasoning [Presentation]. Shenzhen Forum 2024, Shenzhen, China. ( reposiTUm)

Szeider, S. (2024, October 14). Structure-Guided Local Improvement for Maximum Satisfiability [Presentation]. Dagstuhl Seminar 16381, Dagstuhl, Germany. ( reposiTUm)

Szeider, S. (2024, October 15). SAT modulo Symmetries [Presentation]. Dagstuhl Seminar 16381, Dagstuhl, Germany. ( reposiTUm)

Szeider, S. (2023, April 18). Isomorph-Free Generation of Combinatorial Objects with SAT Modulo Symmetries [Presentation]. Extended Reunion: Satisfiability 2023, United States of America (the). ( reposiTUm)

Szeider, S. (2022). SLIM- SAT-based Local Improvement [Conference Presentation]. Dagstuhl Seminar 22411 Theory and Practice of SAT and Combinatorial Solving, Germany. ( reposiTUm)

Szeider, S. (2022). The Parameterized Complexity of SAT [Conference Presentation]. Workshop Parameterized Complexity of Computational Reasoning (PCCR 2022), Israel. ( reposiTUm)

Szeider, S. (2022). From Twin-Width to Propositional Logic and Back [Conference Presentation]. Workshop on Graph Classes, Optimization, and Width Parameters (GROW), Slovenia. http://hdl.handle.net/20.500.12708/153793 ( reposiTUm)

Szeider, S. (2022). SAT-based Local Improvement [Keynote Presentation]. UNRAVEL-LOGICS workshop, Austria. ( reposiTUm)

Szeider, S. (2019). Computational Thinking und ADA.wien. eEducation Fachtagung, Wien, Austria. http://hdl.handle.net/20.500.12708/86955 ( reposiTUm)

Szeider, S., Ganian, R., Kanj, I., & Ordyniak, S. (2019). Parameterized Complexity Results for the Completion and Clustering of Incomplete Data. Kocoon Workshop, Arras, France. http://hdl.handle.net/20.500.12708/86961 ( reposiTUm)

Szeider, S. (2017). Get Satisfaction: Das Erfüllbarkeitsproblem in Theorie und Praxis. 9. Informatiktag 2017, Tu Wien, Austria. http://hdl.handle.net/20.500.12708/86680 ( reposiTUm)

Szeider, S. (2017). Capturing Structure in Instances of the Propositional Satisfiability Problem. ÖMG-DMV-Congress 2017, Salzburg, Austria. http://hdl.handle.net/20.500.12708/86681 ( reposiTUm)

Szeider, S. (2017). Backdoors for Constraint Satisfaction. Workshop Gutin 60, United Kingdom of Great Britain and Northern Ireland (the). http://hdl.handle.net/20.500.12708/86682 ( reposiTUm)

Szeider, S. (2016). Capturing Structure in SAT and Related Problems. International Workshop on Graph Structure and Satisfiability Testing, Bordeaux, France. http://hdl.handle.net/20.500.12708/86383 ( reposiTUm)

Szeider, S. (2016). Capturing Structure in SAT and Related Problems. Theoretical Foundations of SAT Solving Workshop, Toronto, Canada. http://hdl.handle.net/20.500.12708/86384 ( reposiTUm)

Szeider, S. (2015). A Survey on Parameterized Complexity and SAT. Dagstuhl Seminar, Dagstuhl, Germany. http://hdl.handle.net/20.500.12708/86232 ( reposiTUm)

Szeider, S. (2013). SAT Approach to Clique-Width. Workshop on Graph Classes, Optimization, and Width Parameters (GROW), Santorini Island, Greece, EU. http://hdl.handle.net/20.500.12708/85669 ( reposiTUm)

Szeider, S. (2013). Parameterized Complexity. the International SAT/SMT Summer School, Espoo, Finland, EU. http://hdl.handle.net/20.500.12708/85668 ( reposiTUm)

Szeider, S. (2012). The Parameterized Complexity of Propositional Satisfiability. Statistical Mechanics of Unsatisfiability and Glasses, Ferry Stockholm-Mariehamn and Hotel Arkipelag, Mariehamn, Åland, EU. http://hdl.handle.net/20.500.12708/85422 ( reposiTUm)

Szeider, S. (2012). Parameterized Complexity. The Logic and Interactions Winter School, CIRM, Marseille, France, EU. http://hdl.handle.net/20.500.12708/85423 ( reposiTUm)

Szeider, S. (2012). Parameterized Complexity Results for Probabilistic Network Structure Learning. Workshop on Applications of Parameterized Algorithms and Complexit, Warwick, UK, EU. http://hdl.handle.net/20.500.12708/85421 ( reposiTUm)

Fichte, J., & Szeider, S. (2016). Backdoor Trees for Answer Set Programming (DBAI-TR-2016-98). http://hdl.handle.net/20.500.12708/39079 ( reposiTUm)

Dvorak, W., Szeider, S., & Woltran, S. (2012). Abstract Argumentation via Monadic Second Order Logic. (DBAI-TR-2012-79). http://hdl.handle.net/20.500.12708/37417 ( reposiTUm)

Ganian, R., Kalany, M., Szeider, S., & Träff, J. L. (2015). Polynomial-time Construction of Optimal Tree-structured Communication Data Layout Descriptions. arXiv. https://doi.org/10.48550/arXiv.1506.09100 ( reposiTUm)

Pichler, R., Rümmele, S., Szeider, S., & Woltran, S. (2012). Tractable Answer-Set Programming with Weight Constraints: Bounded Treewidth is not Enough. CoRR - Computing Research Repository. https://doi.org/10.48550/arXiv.1204.3040 ( reposiTUm)