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Kanda, N., Boeddeker, C., Heitkaemper, J., Fujita, Y., Horiguchi, S., &; Haeb-Umbach, R. (2019). Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR. In INTERSPEECH 2019, Graz, Austria.
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Gottschalk, S., Rittmeier, F., &; Engels, G. (2019). Intertwined Development of Business Model and Product Functions for Mobile Applications: A Twin Peak Feature Modeling Approach. In S. Hyrynsalmi, M. Suoranta, A. Nguyen-Duc, P. Tyrväinen, &; P. Abrahamsson (Eds.), Software Business (Vol. 370, pp. 192–207). Cham: Springer International Publishing.https://doi.org/10.1007/978-3-030-33742-1_16 
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Rezat, S., Fan, L., Hattermann, M., Schumacher, J., &; Wuschke, H. (Eds.). (2019). Proceedings of the Third International Conference on Mathematics Textbook Research and Development: 16-19 September 2019 Paderborn, Germany. Presented at the Third International Conference on Mathematics Textbook Research and Development, Paderborn: Universitätsbibliothek Paderborn.https://doi.org/10.17619/UNIPB/1-768 
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Schneider, S. B., Peuster, M., Hannemann, K., Behnke, D., Müller, M., Bök, P.-B., &; Karl, H. (2019). “Producing Cloud-Native”: Smart Manufacturing Use Cases on Kubernetes. In IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) Demo Track. Dallas, TX, USA: IEEE.
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Redder, A., Ramaswamy, A., &; Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. Chicago, USA.
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