Search results
Results: 32
Number of items: 32
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Lotfian Delouee, M., Degeler, V., Amthor, P., Schut, M. C., & Koldehofe, B. (2025). Pattern-Level Privacy Protection in Event-Based Systems. SN Computer Science, 6(8), Article 1014. https://doi.org/10.1007/s42979-025-04574-1 -
Karabulut, E., Groth, P., & Degeler, V. (2025). Neurosymbolic Association Rule Mining from Tabular Data. Proceedings of Machine Learning Research, 284, 565-588. https://doi.org/10.48550/arXiv.2504.19354 -
Tello, A., Truong, H., Lazovik, A., & Degeler, V. (2024, May 27). Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11353195
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van Etten, T., Degeler, V., & Luo, D. (2024). Large-Scale Forecasting of Electric Vehicle Charging Demand Using Global Time Series Modeling. In A. Vinel, K. Berns, J. Ploeg, & O. Gusikhin (Eds.), VEHITS 2024: proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems : 2-4 May, 2024, Angers, France (pp. 40-51). SciTePress. https://doi.org/10.5220/0012555400003702 -
Karabulut, E., Groth, P., & Degeler, V. (2024). 3K: Knowledge-Enriched Digital Twin Framework. In Proceedings of the 14th International Conference on the Internet of Things 2024: IoT2024 : Oulu, Finland, 19.-22. Nov 2024 (pp. 188-193). Association for Computing Machinery. https://doi.org/10.1145/3703790.3703834 -
Hadadian Nejad Yousefi, M., Degeler, V., & Lazovik, A. (2024). Self-Adaptive Service Selection for Machine Learning Continuous Delivery. In R. N. Chang, C. K. Chang, Z. Jiang, J. Yang, Z. Jin, M. Sheng, J. Fan, K. Fletcher, Q. He, C. Ardagna, J. Yang, J. Yin, Z. Wang, A. Beheshti, S. Russo, N. Atukorala, J. Wu, P. S. Yu, H. Ludwig, S. Reiff-Marganiec, W. E. Zhang, A. Sailer, N. Bena, K. Li, Y. Watanabe, T. Zhao, S. Wang, Z. Tu, Y. Wang, ... K. Wei (Eds.), 2024 IEEE International Conference on Web Services: IEEE ICWS 2024 : Shenzhen, China, 7-13 July 2024 : proceedings (pp. 1048-1056). IEEE Computer Society. https://doi.org/10.1109/ICWS62655.2024.00123 -
Tello, A., Degeler, V., & Lazovik, A. (2024). Too Good To Be True: accuracy overestimation in (re)current practices for Human Activity Recognition. In 2024 IEEE International Conference on Pervasive Computing and Communications workshops and other affiliated events (PerCom workshops 2024) : Biarritz, France, 11-15 March 2024 (pp. 511-517). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503465 -
Tello, A., Truong, H., Lazovik, A., & Degeler, V. (2024). Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks. Engineering Proceedings, 69, Article 50. https://doi.org/10.3390/engproc2024069050 -
Khalil, A., Lotfian Delouee, M., Degeler, V., Meuser, T., Fernandez Anta, A., & Koldehofe, B. (2024). Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks. In 2024 22nd Mediterranean Communication and Computer Networking Conference: MedComNet 2024 : Nice, France, 11-13 June 2024 (pp. 55-64). IEEE. https://doi.org/10.1109/MedComNet62012.2024.10578208 -
Lotfian Delouee, M., Degeler, V., Amthor, P., & Koldehofe, B. (2024). APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems. In G. Lenzini, P. Mori, & S. Furnell (Eds.), ICISSP 2024: Proceedings of the 10th International Conference on Information Systems Security and Privacy : 26-28 February, 2024, Rome, Italy (pp. 486-497). SciTePress. https://doi.org/10.5220/0012358700003648
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