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Vaz GF. Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems. Universität Paderborn; 2019.
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Mäcker A. On Scheduling with Setup Times. Universität Paderborn; 2019. doi:10.17619/UNIPB/1-828
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Wei Q, Sain B, Wang Y, et al. Simultaneous Spectral and Spatial Modulation for Color Printing and Holography Using All-dielectric Metasurfaces. Nano Letters. 2019;19(12):8964–8971. doi:10.1021/acs.nanolett.9b03957
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Kuhlemann S, Sellmann M, Tierney K. Exploiting Counterfactuals for Scalable Stochastic Optimization. In: Lecture Notes in Computer Science. Cham; 2019. doi:10.1007/978-3-030-30048-7_40
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Dann A, Hermann B, Bodden E. ModGuard: Identifying Integrity &;Confidentiality Violations in Java Modules. IEEE Transactions on Software Engineering. Published online 2019:1-1. doi:10.1109/tse.2019.2931331
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Mair C, Scheffler W, Senger I, Sureth-Sloane C. Analyse der Veränderung der zwischenstaatlichen Gewinnaufteilung bei Einführung einer standardisierten Gewinnverteilungsmethode am Beispiel des Einsatzes von 3D-Druckern. Vol 42.; 2019.
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Hoppe T, Rechbauer M, Sturm S. Steuerkomplexität im Vergleich zwischen Deutschland und Österreich - Eine Analyse des Status quo. Steuer und Wirtschaft. 2019;96(4):397-412.
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Kourouxous T, Bauer T. Violations of Dominance in Decision-Making. Business Research. 2019;12(1):209-239. doi:10.1007/s40685-019-0093-7
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Majdanska A, Wu Y. Using Impact Evaluation to Examine Domestic and International Cooperative Compliance Programs. Tax Notes International. 2019;93(10):1045-1065.
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Ebers L, Hammer M, Berkemeier MB, Menzel A, Förstner J. Coupled microstrip-cavities under oblique incidence of semi-guided waves: a lossless integrated optical add-drop filter. OSA Continuum. 2019;2:3288. doi:10.1364/osac.2.003288
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Couso I, Borgelt C, Hüllermeier E, Kruse R. Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. IEEE Computational Intelligence Magazine. 2019:31-44. doi:10.1109/mci.2018.2881642
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Waegeman W, Dembczynski K, Hüllermeier E. Multi-target prediction: a unifying view on problems and methods. Data Mining and Knowledge Discovery. 2019;33(2):293-324. doi:10.1007/s10618-018-0595-5
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Mortier T, Wydmuch M, Dembczynski K, Hüllermeier E, Waegeman W. Set-Valued Prediction in Multi-Class Classification. In: Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019. ; 2019.
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Ahmadi Fahandar M, Hüllermeier E. Feature Selection for Analogy-Based Learning to Rank. In: Discovery Science. Cham; 2019. doi:10.1007/978-3-030-33778-0_22
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Ahmadi Fahandar M, Hüllermeier E. Analogy-Based Preference Learning with Kernels. In: KI 2019: Advances in Artificial Intelligence. Cham; 2019. doi:10.1007/978-3-030-30179-8_3
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