Dr. rer. nat. E. (Erman) Acar
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute
Bezoekadres
- Science Park 900
Postadres
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Postbus 94323
1090 GH Amsterdam
Contactgegevens
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Publicaties
2024
- Breuer, N. O., Sauter, A. W. M., Mohammadi, M., & Acar, E. (2024). CAGE: Causality-Aware Shapley Value for Global Explanations. In xAI World Conference 2024
- Orzan, N., Acar, E., Grossi, D., & Rădulescu, R. (2024). Learning in Public Goods Games with Non-Linear Utilities: a Multi-Objective Approach. In Proc. of the Adaptive and Learning Agents Workshop (ALA 2024)
- Orzan, N., Acar, E., Radulescu, R., & Grossi, D. (2024). Emergent Cooperation under Uncertain Incentive Alignment. In N. Alechina, V. Dignum, M. Dastani, & J. S. Sichman (Eds.), AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems : May 6-10, 2024, Auckland, New Zealand (pp. 1521-1530). International Foundation for Autonomous Agents and Multiagent Systems.
- Sauter, A. W. M., Boteghi, N., Acar, E., & Plaat, A. (2024). CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning. In N. Alechina, V. Dignum, M. Dastani, & J. S. Sichman (Eds.), AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems : May 6-10, 2024, Auckland, New Zealand (pp. 1664-1672). International Foundation for Autonomous Agents and Multiagent Systems.
- Visbeek, S. K., Acar, E., & den Hengst, F. (2024). Explainable Fraud Detection with Deep Symbolic Classification. In xAI World Conference 2024 https://link.springer.com/content/pdf/10.1007/978-3-031-63800-8_18.pdf?pdf=inline%20link
2023
- Orzan, N., Acar, E., Grossi, D., & Rădulescu, R. (2023). Emergent Cooperation and Deception in Public Good Games. In Proc. of the Adaptive and Learning Agents Workshop (ALA 2023)
Sauter, A., Acar, E., & François-Lavet, V. (2023). A Meta-Reinforcement Learning Algorithm for Causal Discovery. Proceedings of Machine Learning Research, 213, 602-619. https://doi.org/10.48550/arXiv.2207.08457 [details]
2022
- Feng, R., Acar, E., Wang, Y., Schlobach, S., Liu, W., & Ding, W. (2022). Computing Sufficient and Necessary Conditions in CTL: A Forgetting Approach. Information Sciences, 616, 474-504. https://doi.org/10.1016/j.ins.2022.10.124 [details]
- GhadimiAtigh, M., Schoep, J., Acar, E., van Noord, N., & Mettes, P. (2022). Hyperbolic Image Segmentation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 4443-4452). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR52688.2022.00441 [details]
- Ho, L., Acar, E., Arch-int, , S., Schlobach, K. S., & Arch-int, N. (2022). An argumentative approach for handling inconsistency in prioritized Datalog± ontologies. AI Communications.
- Verma, M., & Acar, E. (2022). Learning to Cooperate with Human Evaluative Feedback and Demonstrations. In Proceedings of. HHAI2022: Augmenting Human Intellect
- van Krieken, E., Acar, E., & van Harmelen, F. (2022). Analyzing Differentiable Fuzzy Logic Operators. Artificial Intelligence, 302, Article 103602. https://doi.org/10.1016/j.artint.2021.103602
2024
- Azarm, C., Acar, E., & van Zeelt, M. (2024). On the Potential of Network-Based Features for Fraud Detection. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2402.09495
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Nevenwerkzaamheden
Geen nevenwerkzaamheden
Sauter, A., Acar, E., & François-Lavet, V. (2023). A Meta-Reinforcement Learning Algorithm for Causal Discovery. Proceedings of Machine Learning Research, 213, 602-619.