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169 Publications


2022 | Conference Paper | LibreCat-ID: 34674 | OA
Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey, C.-C., & Doğangün, A. (2022). User Involvement in Training Smart Home Agents. International Conference on Human-Agent Interaction. HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand. https://doi.org/10.1145/3527188.3561914
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2022 | Book Chapter | LibreCat-ID: 37902
Janicki, N. (2022). Entwicklung und Evaluation eines Fortbildungskonzepts im Kontext der technischen Bildung an Grundschulen am Beispiel von Lernrobotern. In M. Binder, C. Wiesmüller, & T. Finkbeiner (Eds.), Technik: Verstehen wir, was wir nutzen!? - Tagungsband zur 23. Jahrestagung der Deutschen Gesellschaft für Technische Bildung in Mannheim vom 24.-25. September 2021. (pp. 266–286).
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2022 | Conference Paper | LibreCat-ID: 40046
Schröer, F., & Tenberge, C. (2022). How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training. In D. Gill, J. Tuff, T. Kennedy, S. Pendergast, & S. Jamil (Eds.), PATT39 - PATT on the Edge Technology, Innovation and Education (pp. 49–57).
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2022 | Journal Article | LibreCat-ID: 36083
Constantiou, I., Mukkamala, A., Sjöklint, M., & Trier, M. (2022). Engaging with self-tracking applications: how do users respond to their performance data? European Journal of Information Systems, 1–21. https://doi.org/10.1080/0960085x.2022.2081096
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2022 | Conference Paper | LibreCat-ID: 31066
Schön, O., Götte, R.-S., & Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24. https://doi.org/10.1016/j.ifacol.2022.07.282
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2022 | Journal Article | LibreCat-ID: 34614
Schloots, F. M. (2022). ‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker. ffk Journal, 6(7), 74–91. https://doi.org/10.25969/MEDIAREP/18238
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2021 | Conference Paper | LibreCat-ID: 25278
Afifi, H., Sauer, F. J., & Karl, H. (2021). Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding. 2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21).
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2021 | Conference Paper | LibreCat-ID: 25281
Afifi, H., Guenther, M., Brendel, A., Karl, H., & Kellermann, W. (2021). Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities. 14. ITG Conference on Speech Communication (ITG 2021).
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2021 | Conference Paper | LibreCat-ID: 20125
Hasnain, A., & Karl, H. (n.d.). Learning Flow Scheduling. In 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC). Las Vegas, USA: IEEE Computer Society. https://doi.org/10.1109/CCNC49032.2021.9369514
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2021 | Journal Article | LibreCat-ID: 28349
Drumm, S., Müller, M., & Stenzel, N. (2021). Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie. Informationen Deutsch als Fremdsprache, 48(5), 496–515. https://doi.org/10.1515/infodaf-2021-0069
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2021 | Conference Paper | LibreCat-ID: 26049
Bäumer, F. S., Kersting, J., Denisov, S., & Geierhos, M. (2021). IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225.
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2021 | Journal Article | LibreCat-ID: 21004
Wever, M. D., Tornede, A., Mohr, F., & Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–1. https://doi.org/10.1109/tpami.2021.3051276
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2021 | Conference Paper | LibreCat-ID: 21005
Hasnain, A., & Karl, H. (n.d.). Learning Coflow Admissions. In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). Vancouver BC Canada: IEEE Communications Society. https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599
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2021 | Conference Paper | LibreCat-ID: 21479
Afifi, H., Ramaswamy, A., & Karl, H. (2021). A Reinforcement Learning QoI/QoS-Aware Approach in Acoustic Sensor Networks. In 2021 IEEE 18th Annual Consumer Communications \& Networking Conference (CCNC) (CCNC 2021).
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2021 | Conference Paper | LibreCat-ID: 21543 | OA
Schneider, S. B., Qarawlus, H., & Karl, H. (2021). Distributed Online Service Coordination Using Deep Reinforcement Learning. In IEEE International Conference on Distributed Computing Systems (ICDCS). Washington, DC, USA: IEEE.
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2021 | Conference Paper | LibreCat-ID: 22481
Sander, T., Lange, S., Hilleringmann, U., Geneis, V., Hedayat, C., Kuhn, H., & Gockel, F.-B. (2021). Detection of Defects on Irregular Structured Surfaces by Image Processing Methods for Feature Extraction. In 22nd IEEE International Conference on Industrial Technology (ICIT). Valencia, Spain : IEEE. https://doi.org/10.1109/icit46573.2021.9453646
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2021 | Journal Article | LibreCat-ID: 21808 | OA
Schneider, S. B., Khalili, R., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., & Hecker, A. (2021). Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. Transactions on Network and Service Management. https://doi.org/10.1109/TNSM.2021.3076503
LibreCat | Files available | DOI
 

2021 | Conference Paper | LibreCat-ID: 27381
Damke, C., & Hüllermeier, E. (2021). Ranking Structured Objects with Graph Neural Networks. In C. Soares & L. Torgo (Eds.), Proceedings of The 24th International Conference on Discovery Science (DS 2021) (Vol. 12986, pp. 166–180). Springer. https://doi.org/10.1007/978-3-030-88942-5
LibreCat | DOI | arXiv
 

2021 | Journal Article | LibreCat-ID: 20212 | OA
Prester, J., Wagner, G., Schryen, G., & Hassan, N. R. (2021). Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach. Decision Support Systems, 140(January), Article 113432.
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2021 | Working Paper | LibreCat-ID: 33854 | OA
Schneider, S. B., Karl, H., Khalili, R., & Hecker, A. (2021). DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning.
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