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130 Publications
2024 | Book Chapter | LibreCat-ID: 52759
O. L. Preuß, J. Rook, and H. Trautmann, “On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems,” in Applications of Evolutionary Computation, Cham: Springer Nature Switzerland, 2024.
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| DOI
2024 | Conference Paper | LibreCat-ID: 52749
M. Vinzent Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” 2024, doi: 10.1109/ssci52147.2023.10372008.
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2023 | Conference Paper | LibreCat-ID: 47522
R. P. Prager et al., “Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features,” in Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023, pp. 129–139, doi: 10.1145/3594805.3607136.
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2023 | Conference Paper | LibreCat-ID: 46297
R. P. Prager and H. Trautmann, “Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features,” in Applications of Evolutionary Computation, 2023, pp. 411–425.
LibreCat
2023 | Conference Paper | LibreCat-ID: 46298
L. Schäpermeier, P. Kerschke, C. Grimme, and H. Trautmann, “Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets,” in Evolutionary Multi-Criterion Optimization, 2023, pp. 291–304.
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2023 | Journal Article | LibreCat-ID: 46299
R. P. Prager and H. Trautmann, “Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python,” Evolutionary Computation, pp. 1–25, 2023, doi: 10.1162/evco_a_00341.
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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: 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 | Conference Paper | LibreCat-ID: 48898
M. V. 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 | Conference Paper | LibreCat-ID: 46307
M. V. 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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2022 | Conference Paper | LibreCat-ID: 46304
R. P. Prager, M. V. Seiler, H. Trautmann, and P. Kerschke, “Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods,” in Parallel Problem Solving from Nature — PPSN XVII, 2022, pp. 3–17, doi: 10.1007/978-3-031-14714-2_1.
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2022 | Conference Paper | LibreCat-ID: 46303
J. S. Pohl, D. Assenmacher, M. V. Seiler, H. Trautmann, and C. Grimme, “Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches,” in Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM), 2022, pp. 1–10, doi: 10.36190/2022.91.
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| DOI
2022 | Conference Paper | LibreCat-ID: 46305
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. 356–359–356–359, doi: 10.1145/3520304.3528998.
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| DOI
2022 | Journal Article | LibreCat-ID: 46309
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. 8, pp. 1–44, 2022, doi: 10.3390/app12189094.
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| DOI
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: 46302
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.
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