Searchable List of Research Output

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  • Aziz, H., Biró, P., Gaspers, S., de Haan, R., Mattei, N., Rastegari, B. (2020) Stable Matching with Uncertain Linear Preferences.
    Algorithmica, Vol. 82 (pp 1410–1433)
  • Aziz, H., de Haan, R., Rastegari, B. (2017) Pareto Optimal Allocation under Compact Uncertain Preferences.
    In Sierra, C. (Eds.), Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17): Melbourne, Australia, 19-25 August 2017 (pp 77-83). International Joint Conferences on Artificial Intelligence.
  • Aziz, H., de Haan, R., Rastegari, B. (2017) Pareto Optimal Allocation under Uncertain Preferences.
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017): Melbourne, Australia 19-25 August 2017 (pp 77-83). International Joint Conferences on Artificial Intelligence.
  • Aziz, H., de Haan, R., Rastegari, B. (2017) Pareto Optimal Allocation under Uncertain Preferences.
    In Das, S. Durfee, E. Larson, K. Winikoff, M. (Eds.), AAMAS '17: proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems : May, 8-12, 2017, São Paulo, Brazil (pp 1472-1474 ). International Foundation for Autonomous Agents and Multiagent Systems.
  • Aziz, H., Rey, S. (2020) Almost Group Envy-free Allocation of Indivisible Goods and Chores.
    In Bessiere, C. (Eds.), Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence: IJCAI-20 : Yokohama (pp 39-45). International Joint Conferences on Artificial Intelligence.
    Conference contribution | https://doi.org/10.24963/ijcai.2020/6 | UvA-DARE
  • Aziz, W. (2015) Grasp: Randomised Semiring Parsing.
    The Prague Bulletin of Mathematical Linguistics, Vol. 104 (pp 51-62)
  • Azzopardi, L., Järvelin, K., Kamps, J., Smucker, M.D. (2010) Report on SIGIR 2010 Workshop on the Simulation of Interaction.
    SIGIR Forum, Vol. 44 (pp 35-47)
  • Azzopardi, L., Järvelin, K., Kamps, J., Smucker, M.D. (2010) Proceedings of the SIGIR 2010 Workshop on the Simulation of Interaction: Automated Evaluation of Interactive IR : Geneva, Switzerland, July 19-23, 2010.
    IR Publications.
    Book (Editorship) | UvA-DARE
  • Baan, J., Aziz, W., Plank, B., Fernández, R. (2022) Stop Measuring Calibration When Humans Disagree.
    In Goldberg, Y. Kozareva, Z. Zhang, Y. (Eds.), Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: December 7-11, 2022, Abu Dhabi, United Arab Emirates (pp 1892–1915). Association for Computational Linguistics.
  • Baan, J., Fernández, R., Plank, B., Aziz, W. (2024) Interpreting Predictive Probabilities: Model Confidence or Human Label Variation?.
    In Graham, Y. Purver, M. (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (pp 268-277). Association for Computational Linguistics.
  • Baan, J., Leible, J., Nikolaus, M., Rau, D., Ulmer, D., Baumgärtner, T., Hupkes, D., Bruni, E. (2019) On the Realization of Compositionality in Neural Networks.
    In Linzen, T. Chrupała, G. Belinkov, Y. Hupkes, D. (Eds.), The BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP at ACL 2019: ACL 2019 : proceedings of the Second Workshop : August 1, 2019, Florence, Italy (pp 127-137). The Association for Computational Linguistics.
    Conference contribution | https://doi.org/10.18653/v1/W19-4814 | UvA-DARE
  • Bachmann, D., Noichl, Maximilian, van Maanen, Leendert, Klein, D. (2025) Exploring complex emergent phenomena with agent-based modeling.
    In Encyclopedia of Measurement in Social Sciences (Reference Module in Social Sciences). Elsevier.
    Entry for encyclopedia/dictionary | https://doi.org/10.1016/B978-0-443-26629-4.00107-6 | UvA-DARE
  • Bachmann, D., van der Wal, O., Chvojka, E., Zuidema, W., van Maanen, L., Schulz, K. (2024) fl-IRT-ing with Psychometrics to Improve NLP Bias Measurement.
    Minds and Machines, Vol. 34
  • Bachmann, D., van Maanen, L. (2024) Towards the application of evidence accumulation models in the design of (semi-)autonomous driving systems – an attempt to overcome the sample size roadblock.
    International Journal of Human-Computer Studies, Vol. 185
  • Bachor, P., Behnke, G. (2024) Learning Planning Domains from Non-redundant Fully-Observed Traces: Theoretical Foundations and Complexity Analysis.
    In Wooldridge, M. Dy, J. Natarajan, S. (Eds.), Proceedings of the 38th AAAI Conference on Artificial Intelligence: AAAI-2024 (pp 20028-20035). AAAI Press.
  • Bachor, P., Dekker, M., Behnke, G. (2025) Is This Plan Necessarily Redundant? On the Computational Complexity of Unobserved Domain Learning.
    In Harabor, Daniel Ramirez, Miquel (Eds.), Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling: November 9-14, 2025, Melbourne, Victoria, Australia (pp 11-20) (ICAPS, Vol. 35). AAAI Press.
  • Backus, A., Cohen, M., Cohn, N., Faber, M., Krahmer, E., Laparle, S., Maier, E., van Miltenburg, E., Roelofsen, F., Sciubba, E., Scholman, M., Shterionov, D., Sie, M., Tomas, F., Vanmassenhove, E., Venhuizen, N., de Vos, C. (2023) Minds: Big questions for linguistics in the age of AI.
    Linguistics in the Netherlands, Vol. 40 (pp 301-308)
  • Bader, S., Hitzler, P., Hölldobler, S., Witzel, S.A. (2007) A Fully Connectionist Model Generator for Covered First-Order Logic Programs.
    In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007) (pp 666-671)
    Conference contribution | UvA-DARE
  • Bader, S., Hitzler, P., Hölldobler, S., Witzel, S.A. (2007) The Core Method: Connectionist Model Generation for First-Order Logic Programs.
    In Hammer, B. Hitzler, P. (Eds.), Perspectives of Neural-Symbolic Integration (pp 205-232) (Studies in Computational Intelligence). Springer.
    Chapter | UvA-DARE
  • Badura, C., Berto, F. (2019) Truth in Fiction, Impossible Worlds, and Belief Revision.
    Australasian Journal of Philosophy, Vol. 97 (pp 178-193)

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