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191 Publications
2020 | Journal Article | LibreCat-ID: 46333
D. Assenmacher, L. Clever, L. Frischlich, T. Quandt, H. Trautmann, and C. Grimme, “Demystifying Social Bots: On the Intelligence of Automated Social Media Actors,” Social Media + Society, vol. 6, no. 3, p. 2056305120939264, 2020, doi: 10.1177/2056305120939264.
LibreCat
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2020 | Journal Article | LibreCat-ID: 46334
J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms,” Applied Soft Computing, vol. 88, p. 105901, 2020, doi: https://doi.org/10.1016/j.asoc.2019.105901.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 46331
M. V. Seiler, H. Trautmann, and P. Kerschke, “Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2020, pp. 1–8, doi: 10.1109/IJCNN48605.2020.9207338.
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2020 | Conference Paper | LibreCat-ID: 46332
V. Steinhoff, P. Kerschke, P. Aspar, H. Trautmann, and C. Grimme, “Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 2445–2452, doi: 10.1109/SSCI47803.2020.9308259.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 48847
J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 1277–1285, doi: 10.1145/3377930.3390174.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 48849
J. Bossek, C. Doerr, P. Kerschke, A. Neumann, and F. Neumann, “Evolving Sampling Strategies for One-Shot Optimization Tasks,” in Parallel Problem Solving from Nature (PPSN XVI), 2020, pp. 111–124, doi: 10.1007/978-3-030-58112-1_8.
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2020 | Conference Paper | LibreCat-ID: 48851
J. Bossek, K. Casel, P. Kerschke, and F. Neumann, “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 1286–1294, doi: 10.1145/3377930.3390243.
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2020 | Conference Paper | LibreCat-ID: 48845
J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 166–174, doi: 10.1145/3377930.3390146.
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2020 | Conference Paper | LibreCat-ID: 48844
J. Bossek, P. Kerschke, and H. Trautmann, “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection,” in 2020 IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8, doi: 10.1109/CEC48606.2020.9185613.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 48850
J. Bossek, C. Doerr, and P. Kerschke, “Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 778–786, doi: 10.1145/3377930.3390155.
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2020 | Conference Paper | LibreCat-ID: 48852
J. Bossek, A. Neumann, and F. Neumann, “Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions,” in Parallel Problem Solving from Nature (PPSN XVI), 2020, pp. 346–359, doi: 10.1007/978-3-030-58112-1_24.
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2020 | Conference Paper | LibreCat-ID: 48846
J. Bossek, C. Grimme, G. Rudolph, and H. Trautmann, “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing,” in 2020 IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8, doi: 10.1109/CEC48606.2020.9185778.
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2020 | Conference Paper | LibreCat-ID: 48879
A. V. Do, J. Bossek, A. Neumann, and F. Neumann, “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 681–689, doi: 10.1145/3377930.3389844.
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2020 | Conference Paper | LibreCat-ID: 48895
V. Roostapour, J. Bossek, and F. 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, 2020, pp. 551–559, doi: 10.1145/3377930.3390168.
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2020 | Conference Paper | LibreCat-ID: 48897
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, and H. 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), 2020, pp. 48–64, doi: 10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 48848
J. Bossek, P. Kerschke, and H. Trautmann, “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms,” Applied Soft Computing, vol. 88, no. C, 2020, doi: 10.1016/j.asoc.2019.105901.
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2020 | Journal Article | LibreCat-ID: 48836
T. Bartz-Beielstein et al., “Benchmarking in Optimization: Best Practice and Open Issues,” Corr, 2020.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46338
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm,” in Evolutionary Multi-Criterion Optimization (EMO), 2019, vol. 11411, pp. 516–528, doi: 10.1007/978-3-030-12598-1_41.
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2019 | Conference Paper | LibreCat-ID: 46343
C. Grimme, P. Kerschke, and H. Trautmann, “Multimodality in Multi-Objective Optimization — More Boon than Bane?,” in Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), 2019, vol. 11411, pp. 126–138, doi: 10.1007/978-3-030-12598-1_11.
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2019 | Journal Article | LibreCat-ID: 46345
P. Kerschke, H. H. Hoos, F. Neumann, and H. Trautmann, “Automated Algorithm Selection: Survey and Perspectives,” Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 3–45, 2019, doi: 10.1162/evco_a_00242.
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