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130 Publications
2024 | Book Chapter | LibreCat-ID: 52759
Preuß OL, Rook J, Trautmann H. On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems. In: Applications of Evolutionary Computation. Springer Nature Switzerland; 2024. doi:10.1007/978-3-031-56852-7_20
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2024 | Conference Paper | LibreCat-ID: 52749
Vinzent Seiler M, Rook J, Heins J, Preuß OL, Bossek J, Trautmann H. Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE; 2024. doi:10.1109/ssci52147.2023.10372008
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2023 | Conference Paper | LibreCat-ID: 47522
Prager RP, Dietrich K, Schneider L, 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. FOGA ’23. Association for Computing Machinery; 2023:129–139. doi:10.1145/3594805.3607136
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2023 | Conference Paper | LibreCat-ID: 46297
Prager RP, Trautmann H. Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features. In: Correia J, Smith S, Qaddoura R, eds. Applications of Evolutionary Computation. Springer Nature Switzerland; 2023:411–425.
LibreCat
2023 | Conference Paper | LibreCat-ID: 46298
Schäpermeier L, Kerschke P, Grimme C, Trautmann H. Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. In: Emmerich M, Deutz A, Wang H, et al., eds. Evolutionary Multi-Criterion Optimization. Springer Nature Switzerland; 2023:291–304.
LibreCat
2023 | Journal Article | LibreCat-ID: 46299
Prager RP, Trautmann H. Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python. Evolutionary Computation. Published online 2023:1–25. doi:10.1162/evco_a_00341
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2023 | Journal Article | LibreCat-ID: 46310
Heins J, Bossek J, Pohl J, Seiler M, Trautmann H, Kerschke P. A study on the effects of normalized TSP features for automated algorithm selection. Theoretical Computer Science. 2023;940:123-145. doi:https://doi.org/10.1016/j.tcs.2022.10.019
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2023 | Conference Paper | LibreCat-ID: 52530
Prager RP, Trautmann H. Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems. In: Silva S, Paquete L, eds. Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023. ACM; 2023:451–454. doi:10.1145/3583133.3590757
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2023 | Conference Paper | LibreCat-ID: 48898
Seiler MV, Rook J, Heins J, Preuß OL, Bossek J, Trautmann H. Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI). ; :361-368. doi:10.1109/SSCI52147.2023.10372008
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2022 | Book Chapter | LibreCat-ID: 46300
Niemann M, Assenmacher D, Brunk J, Riehle DM, Becker J, Trautmann H. (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In: Weitzel G, Mündges S, eds. Hate Speech — Definitionen, Ausprägungen, Lösungen. VS Verlag für Sozialwissenschaften; 2022:249–274. doi:10.1007/978-3-658-35658-3_13
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2022 | Conference Paper | LibreCat-ID: 46301
Assenmacher D, Trautmann H. Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption. In: et al. Tran T, ed. Intelligent Information and Database Systems. Springer International Publishing; 2022:3–16. doi:10.1007/978-3-031-21743-2_1
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2022 | Journal Article | LibreCat-ID: 46316
Assenmacher D, Weber D, Preuss M, et al. Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review. 2022;40(6):1496-1522. doi:10.1177/08944393211012268
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2022 | Conference Paper | LibreCat-ID: 46306
Schneider L, Schäpermeier L, Prager RP, Bischl B, Trautmann H, Kerschke P. HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. Parallel Problem Solving from Nature — PPSN XVII. Springer International Publishing; 2022:575–589. doi:10.1007/978-3-031-14714-2_40
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2022 | Conference Paper | LibreCat-ID: 46307
Seiler MV, Prager RP, Kerschke P, Trautmann H. 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. Association for Computing Machinery; 2022:657–665. doi:10.1145/3512290.3528834
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2022 | Conference Paper | LibreCat-ID: 46304
Prager RP, Seiler MV, Trautmann H, Kerschke P. Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. Parallel Problem Solving from Nature — PPSN XVII. Springer International Publishing; 2022:3–17. doi:10.1007/978-3-031-14714-2_1
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2022 | Conference Paper | LibreCat-ID: 46303
Pohl JS, Assenmacher D, Seiler MV, Trautmann H, Grimme C. Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In: the Advancement of Artificial Intelligence (AAAI) Association for, ed. Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM). AAAI Press; 2022:1–10. doi:10.36190/2022.91
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2022 | Conference Paper | LibreCat-ID: 46305
Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Fieldsend J, Wagner M, eds. Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO ’22. Association for Computing Machinery; 2022:356–359-356–359. doi:10.1145/3520304.3528998
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2022 | Journal Article | LibreCat-ID: 46309
Clever L, Pohl JS, Bossek J, Kerschke P, Trautmann H. Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences. 2022;12(8):1–44. doi:10.3390/app12189094
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2022 | Journal Article | LibreCat-ID: 46308
Aspar P, Steinhoff V, Schäpermeier L, Kerschke P, Trautmann H, Grimme C. The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. Natural Computing. 2022;1:1–15. doi:10.1007/s11047-022-09919-w
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2022 | Conference Paper | LibreCat-ID: 46302
Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova A, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. Parallel Problem Solving from Nature — PPSN XVII. Springer International Publishing; 2022:192–206.
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