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J. Castenow, P. Kling, T. Knollmann, and F. Meyer auf der Heide, “A Discrete and Continuous Study of the Max-Chain-Formation Problem – Slow Down to Speed Up,” in Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings, 2020, vol. 12514, pp. 65–80.
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C. Damke, V. Melnikov, and E. Hüllermeier, “A Novel Higher-order Weisfeiler-Lehman Graph Convolution,” in Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020), Bangkok, Thailand, 2020, vol. 129, pp. 49–64.
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C.-M. Kuball, B. Uhe, G. Meschut, and M. Merklein, Eds., Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel, vol. 50. 2020, pp. 280–285.
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S. Mayer, Optimierung von JMCTest beim Testen von Inter Method Contracts. Universität Paderborn, 2020.
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Z. Nouri, H. Wachsmuth, and G. Engels, “Mining Crowdsourcing Problems from Discussion Forums of Workers,” in Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, Barcelona, Spain, pp. 6264–6276.
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R. El Baff, K. Al-Khatib, B. Stein, and H. Wachsmuth, “Persuasiveness of News Editorials depending on Ideology and Personality,” in Third Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES 2020), 2020, pp. 29–40.
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B. Herzig, A. Martin, and T.-M. Klar, “Mobile Medien – Medienpädagogische und technische Grundlagen, Potential für den Deutschunterricht und Beispiele.,” in Deutsch Digital. Band 1 Theorie (2. Aufl.), J. Knopf and U. Abraham, Eds. 2020, pp. 108–135.
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D. Kundisch and D. Beverungen, Als Wirtschaftsinformatiker die digitale Transformation in Organisationen gestalten. Martin, Slovakia, 2020, pp. 22–26.
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M. Spliethöver and H. Wachsmuth, “Argument from Old Man’s View: Assessing Social Bias in Argumentation,” in Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 76–87.
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J. Dorsch and H. Wachsmuth, “Semi-Supervised Cleansing of Web Argument Corpora,” in Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 19–29.
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M. Otroshi and G. Meschut, Methodenentwicklung zur Schädigungsmodellierung für die numerische Prozesssimulation mechanischer Fügeverfahren. Europäische Forschungsgesellschaft für Blechverarbeitung e.V., 2020.
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L. Masendorf, M. Wächter, S. Horstmann, M. Otroshi, A. Esderts, and G. Meschut, “Linear damage accumulation of self-pierce riveted joints,” presented at the Fourth International Conference on Material and Component Performance under Variable Amplitude Loading, Darmstadt, Germany, 2020.
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S. Baswana, S. Gupta, and T. Knollmann, “Mincut Sensitivity Data Structures for the Insertion of an Edge,” in 28th Annual European Symposium on Algorithms (ESA 2020), 2020, vol. 173, pp. 12:1-12:14.
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H. Afifi and H. Karl, “Reinforcement Learning for Virtual Network Embedding in Wireless Sensor Networks,” in 2020 Thirteenth International Workshop on Selected Topics in Mobile and Wireless Computing (STWiMob’2020), 2020.
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A. Bondarenko et al., “Overview of Touché 2020: Argument Retrieval,” in CEUR Workshop Proceedings, 2020, vol. 2696, pp. 384–395.
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M. Otroshi and G. Meschut, “Spannungszustandsabhängige Schädigungsmodellierung zum Halbhohlstanznieten,” Umformtechnik Blech Rohre Profile, no. 7/20, pp. 48–50, 2020.
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