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204 Publications
2023 | Conference Paper | LibreCat-ID: 48872
J. Bossek and D. Sudholt, “Runtime Analysis of Quality Diversity Algorithms,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2023, pp. 1546–1554, doi: 10.1145/3583131.3590383.
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2023 | Conference Paper | LibreCat-ID: 48886
A. Marrero, E. Segredo, E. Hart, J. Bossek, and A. Neumann, “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space,” in Proceedings of the Genetic} and Evolutionary Computation Conference, 2023, pp. 312–320, doi: 10.1145/3583131.3590504.
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2023 | Journal Article | LibreCat-ID: 48871
J. Bossek and D. Sudholt, “Do Additional Target Points Speed Up Evolutionary Algorithms?,” Theoretical Computer Science, p. 113757, 2023, doi: 10.1016/j.tcs.2023.113757.
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2023 | Journal Article | LibreCat-ID: 48859
J. Bossek and C. Grimme, “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem,” Evolutionary Computation, pp. 1–35, 2023, doi: 10.1162/evco_a_00335.
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2023 | Conference Paper | LibreCat-ID: 52530
R. P. Prager and H. Trautmann, “Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems,” in Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023, 2023, pp. 451–454, doi: 10.1145/3583133.3590757.
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2023 | Journal Article | LibreCat-ID: 46310
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “A study on the effects of normalized TSP features for automated algorithm selection,” Theoretical Computer Science, vol. 940, pp. 123–145, 2023, doi: https://doi.org/10.1016/j.tcs.2022.10.019.
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2023 | Conference Paper | LibreCat-ID: 48898
M. Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” in 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 361–368, doi: 10.1109/SSCI52147.2023.10372008.
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2022 | Book Chapter | LibreCat-ID: 46300
M. Niemann, D. Assenmacher, J. Brunk, D. M. Riehle, J. Becker, and H. Trautmann, “(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse,” in Hate Speech — Definitionen, Ausprägungen, Lösungen, G. Weitzel and S. Mündges, Eds. Wiesbaden: VS Verlag für Sozialwissenschaften, 2022, pp. 249–274.
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2022 | Conference Paper | LibreCat-ID: 46301
D. Assenmacher and H. Trautmann, “Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption,” in Intelligent Information and Database Systems, 2022, pp. 3–16, doi: 10.1007/978-3-031-21743-2_1.
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2022 | Journal Article | LibreCat-ID: 46316
D. Assenmacher et al., “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem,” Social Science Computer Review, vol. 40, no. 6, pp. 1496–1522, 2022, doi: 10.1177/08944393211012268.
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2022 | Conference Paper | LibreCat-ID: 46306
L. Schneider, L. Schäpermeier, R. P. Prager, B. Bischl, H. Trautmann, and P. Kerschke, “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis,” in Parallel Problem Solving from Nature — PPSN XVII, 2022, pp. 575–589, doi: 10.1007/978-3-031-14714-2_40.
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2022 | Journal Article | LibreCat-ID: 46308
P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, and C. Grimme, “The objective that freed me: a multi-objective local search approach for continuous single-objective optimization,” Natural Computing, vol. 1, pp. 1–15, 2022, doi: 10.1007/s11047-022-09919-w.
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2022 | Conference Paper | LibreCat-ID: 48861
J. Bossek and F. Neumann, “Exploring the Feature Space of TSP Instances Using Quality Diversity,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2022, pp. 186–194, doi: 10.1145/3512290.3528851.
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2022 | Conference Paper | LibreCat-ID: 48868
J. Bossek, A. Neumann, and F. Neumann, “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 824–842, doi: 10.1145/3520304.3533626.
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2022 | Conference Paper | LibreCat-ID: 48882
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 192–206, doi: 10.1007/978-3-031-14714-2_14.
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2022 | Conference Paper | LibreCat-ID: 48894
A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.
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2022 | Journal Article | LibreCat-ID: 48878
L. Clever, J. S. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Process-Oriented Stream Classification Pipeline: A Literature Review,” Applied Sciences, vol. 12, no. 18, p. 9094, 2022, doi: 10.3390/app12189094.
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2022 | Conference Paper | LibreCat-ID: 48896
J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 356–359, doi: 10.1145/3520304.3528998.
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2022 | Journal Article | LibreCat-ID: 52532
A. S. Rodrigues et al., “Estimation of component reliability from superposed renewal processes by means of latent variables,” Comput. Stat., vol. 37, no. 1, pp. 355–379, 2022, doi: 10.1007/S00180-021-01124-0.
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2022 | Conference Paper | LibreCat-ID: 46307
M. Seiler, R. P. Prager, P. Kerschke, and H. Trautmann, “A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2022, pp. 657–665, doi: 10.1145/3512290.3528834.
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