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1556 Publications


2019 | Journal Article | LibreCat-ID: 4562
Hippert, Benjamin, et al. “Portfolio Benefits of Adding Corporate Credit Default Swap Indices: Evidence from North America and Europe.” Review of Derivatives Research , vol. 22, no. 2, 2019, pp. 203–59, doi:https://doi.org/10.1007/s11147-018-9148-8.
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2019 | Journal Article | LibreCat-ID: 19300
Mäck, Markus, et al. “Optimization with Constraints Considering Polymorphic Uncertainties.” GAMM-Mitteilungen, e201900005, 2019, doi:10.1002/gamm.201900005.
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2019 | Journal Article | LibreCat-ID: 27026
Libuda, Lars, et al. “Vitamin D and the Risk of Depression: A Causal Relationship? Findings from a Mendelian Randomization Study.” Nutrients, 1085, 2019, doi:10.3390/nu11051085.
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2019 | Journal Article | LibreCat-ID: 27025
Knoll-Pientka, Nadja, et al. “Risk Factors for a Low Weight Gain in the Early Stage of Adolescent Anorexia Nervosa Inpatient Treatment: Findings from a Pilot Study.” Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity, 2019, pp. 911–19, doi:10.1007/s40519-019-00705-9.
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2019 | Journal Article | LibreCat-ID: 27521
Hebebrand, Johannes, et al. “Clinical Trials Required to Assess Potential Benefits and Side Effects of Treatment of Patients With Anorexia Nervosa With Recombinant Human Leptin.” Frontiers in Psychology, 2019, doi:10.3389/fpsyg.2019.00769.
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2019 | Journal Article | LibreCat-ID: 47947
Rüsing, Michael, et al. “Toward 3D Integrated Photonics Including Lithium Niobate Thin Films: A Bridge Between Electronics, Radio Frequency, and Optical Technology.” IEEE Nanotechnology Magazine, vol. 13, no. 4, Institute of Electrical and Electronics Engineers (IEEE), 2019, pp. 18–33, doi:10.1109/mnano.2019.2916115.
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2019 | Conference Paper | LibreCat-ID: 46343
Grimme, Christian, et al. “Multimodality in Multi-Objective Optimization — More Boon than Bane?” Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), edited by Kalyanmoy Deb et al., vol. 11411, Springer, 2019, pp. 126–138, doi:10.1007/978-3-030-12598-1_11.
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2019 | Conference Paper | LibreCat-ID: 46342
Grimme, Christian, et al. “Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization.” AIP Conference Proceedings, AIP Publishing, 2019, pp. 020052-1-020052–54, doi:10.1063/1.5090019.
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2019 | Book Chapter | LibreCat-ID: 48341
Wille, Manuel. “Prinzipien Und Strategien Der Textgliederung in Den Zeitungen Des 18. Jahrhunderts – Eine Computerbasierte Korpusanalyse.” Textgliederungsprinzipien. Ihre Kennzeichnungsformen Und Funktionen Vom 8. Bis 18. Jahrhundert. Akten Zum Internationalen Kongress Vom 22. Bis 24. Juni 2017 an Der Universität St. Petersburg, edited by Franz Simmler and Galina Baeva, vol. 34, Weidler, 2019, pp. 507–31.
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2019 | Book Chapter | LibreCat-ID: 31142
Schuster, Britt-Marie. “Textgliederungsprinzipien und Beziehungsgestaltung im Stammbuch von 1559–1878.” Textgliederungsprinzipien. Ihre Kennzeichnungsformen und Funktionen in Texten vom 8. bis 18. Jahrhundert. Akten zum Internationalen Kongress an der Staatlichen Universität St. Petersburg vom 22. bis 24. Juni 2017, edited by Franz Simmler and Galina Baeva, WEIDLER, 2019, pp. 293–312.
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2019 | Book Chapter | LibreCat-ID: 46336
Kerschke, Pascal, and Heike Trautmann. “Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package Flacco.” Applications in Statistical Computing, edited by Nadja Bauer et al., Springer, 2019, pp. 93–123, doi:10.1007/978-3-030-25147-5_7.
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2019 | Journal Article | LibreCat-ID: 46346
Kerschke, Pascal, and Heike Trautmann. “Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning.” Evolutionary Computation (ECJ), vol. 27, no. 1, 2019, pp. 99–127, doi:10.1162/evco_a_00236.
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2019 | Journal Article | LibreCat-ID: 46347
Kerschke, Pascal, et al. “Search Dynamics on Multimodal Multi-Objective Problems.” Evolutionary Computation (ECJ), vol. 27, no. 4, 2019, pp. 577–609, doi:10.1162/evco_a_00234.
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2019 | Conference Paper | LibreCat-ID: 23720
Gräßler, Iris, et al. “Unterstützung des Lernens für kritische Situationen: Potenzial von Augmented Reality für die Instandsetzung auf See.” Go-3D 2019 “Mit 3D Richtung Maritim 4.0” - Tagungsband zur Konferenz Go-3D 2019, edited by Uwe Lukas et al., Fraunhofer Verlag, 2019, pp. 45–57.
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2019 | Conference Paper | LibreCat-ID: 48841
Bossek, Jakob, et al. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm.” Evolutionary Multi-Criterion Optimization (EMO), edited by Kalyanmoy Deb et al., Springer International Publishing, 2019, pp. 516–528, doi:10.1007/978-3-030-12598-1_41.
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2019 | Conference Paper | LibreCat-ID: 48842
Bossek, Jakob, et al. “Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators.” Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2019, pp. 58–71, doi:10.1145/3299904.3340307.
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2019 | Conference Paper | LibreCat-ID: 48843
Bossek, Jakob, et al. “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2019, pp. 1443–1451, doi:10.1145/3321707.3321792.
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2019 | Conference Paper | LibreCat-ID: 48840
Bossek, Jakob, et al. “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2019, pp. 516–523, doi:10.1145/3321707.3321818.
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2019 | Conference Paper | LibreCat-ID: 48858
Bossek, Jakob, and Christian Grimme. “Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-Criteria Shortest Path Problems.” Learning and Intelligent Optimization, edited by Roberto Battiti et al., Springer International Publishing, 2019, pp. 184–198, doi:10.1007/978-3-030-05348-2_17.
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2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” Learning and Intelligent Optimization, edited by Roberto Battiti et al., Springer International Publishing, 2019, pp. 215–219, doi:10.1007/978-3-030-05348-2_19.
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