Pernpeintner, M. (2021). Toward a self-learning governance loop for competitive multi-attribute MAS.
In , AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems : Richland, SC, Virtual Event United Kingdom, May, 2021 (S. 1619-1621). ,
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Wilken, N., Stuckenschmidt, H. und Bartelt, C. (2021). Combining symbolic and data-driven methods for goal recognition.
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2020
Burzlaff, F., Bongarth, B., Grottker, S., Hammen, J. und Bartelt, C. (2020). MergePoint: A graphical web-app for merging HTTP-endpoints and IoT-platform models.
In , 53rd Hawaii International Conference on System Sciences, HICSS 2020 : Maui, Hawaii, USA, January 7-10, 2020 (S. 1-10). Proceedings of the 53rd Hawaii International Conference on System Sciences,
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Pernpeintner, M. (2020). Achieving emergent governance in competitive multi-agent systems.
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Schreckenberger, C., Bartelt, C. und Stuckenschmidt, H. (2020). Robust decision tree induction from unreliable data sources.
In , STAIRS 2020 : Proceedings of the 9th European Starting AI Researchers' Symposium 2020 co-located with 24th European Conference on Artificial Intelligence (ECAI 2020) Santiago Compostela, Spain, August, 2020 (S. Paper 6, 1-8). CEUR Workshop Proceedings,
RWTH: Aachen.
Schreckenberger, C., Bartelt, C. und Stuckenschmidt, H. (2020). Tree-based learning for dynamic data streams.
PhD Forum, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020, Online.
Schreckenberger, C., Glockner, T., Stuckenschmidt, H. und Bartelt, C. (2020). Restructuring of Hoeffding trees for Trapezoidal Data Streams.
In , 20th IEEE International Conference on Data Mining Workshops : 17-20 November 2020, Virtual Conference : Proceedings (S. 416-423). ,
IEEE: Los Alamitos, CA [u.a.].
Burzlaff, F., Ackel, M. und Bartelt, C. (2019). A mapping language for IoT device descriptions.
In , 2019 IEEE 43rd Annual Computer Software and Applications Conference : 15-19 July 2019, Milwaukee, Wisconsin : proceedings (S. 115-120). ,
IEEE Computer Society: Piscataway, NJ.
Schreckenberger, C., Bartelt, C. und Stuckenschmidt, H. (2019). Enhancing a crowd-based delivery network with mobility predictions.
In , PredictGIS'19 : Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility : Chicago, IL, USA, November 05, 2019 (S. 66-75). Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility,
ACM: New York, NY.
Schreckenberger, C., Bartelt, C. und Stuckenschmidt, H. (2019). iDropout: Leveraging deep taylor decomposition for the robustness of deep neural networks.
In , On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings (S. 113-126). Lecture Notes in Computer Science,
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Schreckenberger, C., Beckmann, S. und Bartelt, C. (2019). Next place prediction: A systematic literature review.
In , PredictGIS 2018 : Proceedings of the 2nd ACM SIGSPATIAL Workshop on Prediction of Human Mobility : ACM GIS 2018 Conference: November 6 - November 9, 2018, Seattle, Washington (S. 37-45). Proceedings of the 2Nd ACM SIGSPATIAL Workshop on Prediction of Human Mobility,
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Burzlaff, F., Bartelt, C. und Jacobs, S. (2018). Executing model-based software development for embedded I4.0 devices properly.
In , MOD-WS 2018 : Joint Proceedings of the Workshops at Modellierung 2018 co-located with Modellierung 2018, Braunschweig, Germany, February 21, 2018 (S. 35-46). CEUR Workshop Proceedings,
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Burzlaff, F., Bartelt, C. und Stuckenschmidt, H. (2018). Next steps in knowledge-driven architecture composition.
In , LWDA 2018 : Proceedings of the Conference "Lernen, Wissen, Daten, Analysen" Mannheim, Germany, August 22-24, 2018 (S. 78-83). CEUR Workshop Proceedings,
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2017
Achichi, M., Cheatham, M., Dragisic, Z., Euzenat, J., Faria, D., Ferrara, A., Flouris, G., Fundulaki, I., Harrow, I., Ivanova, V., Jiménez-Ruiz, E., Kolthoff, K., Kuss, E., Lambrix, P., Leopold, H., Li, H., Meilicke, C., Mohammadi, M., Montanelli, S., Pesquita, C., Saveta, T., Shvaiko, P., Splendiani, A., Stuckenschmidt, H., Thiéblin, E., Todorov, K., Trojahn, C. und Zamazal, O. (2017). Results of the Ontology Alignment Evaluation Initiative 2017.
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Burzlaff, F. (2017). Knowledge-driven architecture composition.
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Atkinson, C., Gerbig, R. und Metzger, N. (2015). On the execution of deep models.
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Kolthoff, K. und Dutta, A. (2015). Semantic relation composition in large scale knowledge bases.
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