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204 Publications
2020 | Conference Paper | LibreCat-ID: 48895
Roostapour, Vahid, Jakob Bossek, and Frank Neumann. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 551–559. {GECCO} ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390168.
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88, no. C (2020). https://doi.org/10.1016/j.asoc.2019.105901.
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2020 | Journal Article | LibreCat-ID: 48836
Bartz-Beielstein, Thomas, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, et al. “Benchmarking in Optimization: Best Practice and Open Issues.” Corr, 2020.
LibreCat
2020 | Conference Paper | LibreCat-ID: 46331
Seiler, Moritz, Heike Trautmann, and Pascal Kerschke. “Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries.” In Proceedings of the International Joint Conference on Neural Networks (IJCNN), 1–8. Glasgow, UK, 2020. https://doi.org/10.1109/IJCNN48605.2020.9207338.
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2020 | Conference Paper | LibreCat-ID: 46330
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI), edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, and Heike Trautmann, 48–64. Leiden, The Netherlands, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 46334
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88 (2020): 105901. https://doi.org/10.1016/j.asoc.2019.105901.
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2020 | Conference Paper | LibreCat-ID: 46322
Bossek, Jakob, Christian Grimme, Günter Rudolph, and Heike Trautmann. “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing.” In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, UK, 2020. https://doi.org/10.1109/CEC48606.2020.9185778.
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2020 | Conference Paper | LibreCat-ID: 46324
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.” In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, UK: IEEE, 2020.
LibreCat
2020 | Conference Paper | LibreCat-ID: 46323
Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective Routing of Multiple Vehicles.” In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 166–174. Cancun, Mexico: ACM, 2020.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46343
Grimme, Christian, Pascal Kerschke, and Heike Trautmann. “Multimodality in Multi-Objective Optimization — More Boon than Bane?” In Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), edited by Kalyanmoy Deb, Erik Goodman, Coello Carlos A. Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 11411:126–138. Lecture Notes in Computer Science. East Lansing, MI, USA: Springer, 2019. https://doi.org/10.1007/978-3-030-12598-1_11.
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2019 | Journal Article | LibreCat-ID: 46345
Kerschke, Pascal, Holger H Hoos, Frank Neumann, and Heike Trautmann. “Automated Algorithm Selection: Survey and Perspectives.” Evolutionary Computation (ECJ) 27, no. 1 (2019): 3–45. https://doi.org/10.1162/evco_a_00242.
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2019 | Journal Article | LibreCat-ID: 46344
Carnein, Matthias, and Heike Trautmann. “Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms.” Business and Information Systems Engineering (BISE) 61, no. 3 (2019): 277–297.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46340
Carnein, Matthias, Leschek Homann, Heike Trautmann, and Gottfried Vossen. “A Recommender System Based on Omni-Channel Customer Data.” In Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 65–74. Moscow, Russia, 2019.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46341
Carnein, Matthias, and Heike Trautmann. “Customer Segmentation Based on Transactional Data Using Stream Clustering.” In Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), 280–292. Macau, China, 2019.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46342
Grimme, Christian, Pascal Kerschke, Michael T M Emmerich, Mike Preuss, André H Deutz, and Heike Trautmann. “Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization.” In AIP Conference Proceedings, 020052-1-020052–54. Leiden, The Netherlands: AIP Publishing, 2019. https://doi.org/10.1063/1.5090019.
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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.” In Applications in Statistical Computing, edited by Nadja Bauer, Katja Ickstadt, Karsten Lübke, Gero Szepannek, Heike Trautmann, and Maurizio Vichi, 93–123. Springer, 2019. https://doi.org/10.1007/978-3-030-25147-5_7.
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2019 | Book | LibreCat-ID: 46335
Trautmann, Heike. Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement. Studies in Classification, Data Analysis, and Knowledge Organization. Springer International Publishing, 2019.
LibreCat
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) 27, no. 1 (2019): 99–127. https://doi.org/10.1162/evco_a_00236.
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2019 | Journal Article | LibreCat-ID: 46347
Kerschke, Pascal, Hao Wang, Mike Preuss, Christian Grimme, André Deutz, Heike Trautmann, and Michael Emmerich. “Search Dynamics on Multimodal Multi-Objective Problems.” Evolutionary Computation (ECJ) 27, no. 4 (2019): 577–609. https://doi.org/10.1162/evco_a_00234.
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