Pai, Arathi. Computationally Efficient Modelling and Precision Position and Force Control of SMA Actuators. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2019.
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Schubert, Philipp, et al. “Know Your Analysis: How Instrumentation Aids Understanding Static Analysis.”10.1145/3315568.3329965__Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis  - SOAP 2019, 2019, doi:10.1145/3315568.3329965.
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Gausemeier, Jürgen. Vorausschau und Technologieplanung. 14. Symposium für Vorausschau und Technologieplanung, Heinz Nixdorf Institut, 8. und 9. November 2018. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Weber, Jens. Modellbasierte Werkstück- und Werkzeugpositionierung zur Reduzierung der Zykluszeit in NC-Programmen. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Kage, Martin. Systematik zur Positionierung in technologieinduzierten Wertschöpfungsnetzwerken. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Dülme, Christian. Systematik zur zukunftsorientierten Konsolidierung variantenreicher Produktprogramme. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Schneider, Marcel. Spezifikationstechnik zur Beschreibung und Analyse von Wertschöpfungssystemen. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Echterhoff, Benedikt. Methodik zur Einführung innovativer Geschäftsmodelle in etablierten Unternehmen. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
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Mohr, Felix, et al. “ML-Plan: Automated Machine Learning via Hierarchical Planning.”10.1007/s10994-018-5735-z__Machine Learning, Springer, 2018, pp. 1495–515, doi:10.1007/s10994-018-5735-z.
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Wever, Marcel Dominik, et al. Automated Multi-Label Classification Based on ML-Plan. Arxiv, 2018.
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Mohr, Felix, et al. Automated Machine Learning Service Composition. 2018.
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Graessler, Iris, et al. “SEMI-AUTOMATIZED ASSESSMENT OF REQUIREMENT INTERRELATIONS.”10.21278/idc.2018.0298__Proceedings of the DESIGN 2018 15th International Design Conference, 2018, doi:10.21278/idc.2018.0298.
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Abiteboul, S., et al., editors. Research Directions for Principles of Data Management. Vol. 7, no. 1, 2018, pp. 1–29.
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Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” Frontiers in Computational Intelligence, edited by Sanaz Mostaghim et al., Springer, 2018, pp. 31–46.
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Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning, vol. 107, no. 5, 2018, pp. 903–41.
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Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–58.
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El Mesaoudi-Paul, Adil, et al. “Ranking Distributions Based on Noisy Sorting.” Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–77.
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Hesse, M., et al. “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.
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