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197 Publications
2024 | Journal Article | LibreCat-ID: 54548
Prager, R. P., & Trautmann, H. (2024). Exploratory Landscape Analysis for Mixed-Variable Problems. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3399560
LibreCat
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2024 | Conference Paper | LibreCat-ID: 54642
Dietrich, K., Prager, R., Doerr, C., & Trautmann, H. (2024). Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization. In M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tušar, P. Machado, & T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII (pp. 1–14). Springer International Publishing.
LibreCat
2024 | Conference Paper | LibreCat-ID: 54643
Seiler, M., Skvorc, U., Cenikj, G., Doerr, C., & Trautmann, H. (2024). Learned Features vs. Classical ELA on Affine BBOB Functions. In M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tušar, P. Machado, & T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII (pp. 1–14). Springer International Publishing.
LibreCat
2024 | Book Chapter | LibreCat-ID: 52759
Preuß, O. L., Rook, J., & Trautmann, H. (2024). On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems. In Applications of Evolutionary Computation. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56852-7_20
LibreCat
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2024 | Conference Paper | LibreCat-ID: 52749
Seiler, M., Rook, J., Heins, J., Preuß, O. L., Bossek, J., & Trautmann, H. (2024). Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. 2023 IEEE Symposium Series on Computational Intelligence (SSCI). https://doi.org/10.1109/ssci52147.2023.10372008
LibreCat
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2024 | Conference Paper | LibreCat-ID: 58335
Seiler, M., Skvorc, U., Doerr, C., & Trautmann, H. (2024). Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection. In P. Festa, D. Ferone, T. Pastore, & O. Pisacane (Eds.), Learning and Intelligent Optimization - 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers (Vol. 14990, pp. 361–376). Springer. https://doi.org/10.1007/978-3-031-75623-8_29
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2024 | Conference (Editor) | LibreCat-ID: 58338
Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T., Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III (Vol. 15150). Springer. https://doi.org/10.1007/978-3-031-70071-2
LibreCat
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2024 | Conference (Editor) | LibreCat-ID: 58336
Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T., Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I (Vol. 15148). Springer. https://doi.org/10.1007/978-3-031-70055-2
LibreCat
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2024 | Conference (Editor) | LibreCat-ID: 58339
Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T., Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV (Vol. 15151). Springer. https://doi.org/10.1007/978-3-031-70085-9
LibreCat
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2023 | Conference Paper | LibreCat-ID: 47522
Prager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke, P., Trautmann, H., & Mersmann, O. (2023). Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 129–139. https://doi.org/10.1145/3594805.3607136
LibreCat
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2023 | Conference Paper | LibreCat-ID: 46297
Prager, R. P., & Trautmann, H. (2023). Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation (pp. 411–425). Springer Nature Switzerland.
LibreCat
2023 | Conference Paper | LibreCat-ID: 46298
Schäpermeier, L., Kerschke, P., Grimme, C., & Trautmann, H. (2023). Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. In M. Emmerich, A. Deutz, H. Wang, A. V. Kononova, B. Naujoks, K. Li, K. Miettinen, & I. Yevseyeva (Eds.), Evolutionary Multi-Criterion Optimization (pp. 291–304). Springer Nature Switzerland.
LibreCat
2023 | Journal Article | LibreCat-ID: 46299
Prager, R. P., & Trautmann, H. (2023). Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python. Evolutionary Computation, 1–25. https://doi.org/10.1162/evco_a_00341
LibreCat
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2023 | Conference Paper | LibreCat-ID: 48869
Bossek, J., Neumann, A., & Neumann, F. (2023). On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 248–256. https://doi.org/10.1145/3583131.3590384
LibreCat
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2023 | Conference Paper | LibreCat-ID: 48872
Bossek, J., & Sudholt, D. (2023). Runtime Analysis of Quality Diversity Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference, 1546–1554. https://doi.org/10.1145/3583131.3590383
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2023 | Conference Paper | LibreCat-ID: 48886
Marrero, A., Segredo, E., Hart, E., Bossek, J., & Neumann, A. (2023). Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space. Proceedings of the Genetic} and Evolutionary Computation Conference, 312–320. https://doi.org/10.1145/3583131.3590504
LibreCat
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2023 | Journal Article | LibreCat-ID: 48871
Bossek, J., & Sudholt, D. (2023). Do Additional Target Points Speed Up Evolutionary Algorithms? Theoretical Computer Science, 113757. https://doi.org/10.1016/j.tcs.2023.113757
LibreCat
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2023 | Journal Article | LibreCat-ID: 48859
Bossek, J., & Grimme, C. (2023). On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem. Evolutionary Computation, 1–35. https://doi.org/10.1162/evco_a_00335
LibreCat
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2023 | Conference Paper | LibreCat-ID: 52530
Prager, R. P., & Trautmann, H. (2023). Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems. In S. Silva & L. Paquete (Eds.), Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023 (pp. 451–454). ACM. https://doi.org/10.1145/3583133.3590757
LibreCat
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2023 | Conference Paper | LibreCat-ID: 52863
Ŝkvorc, U., Eftimov, T., & Koro]ec, P. (2023). Analyzing the Generalizability of Automated Algorithm Selection: A Case Study for Numerical Optimization. 2023 IEEE Symposium Series on Computational Intelligence (SSCI). https://doi.org/10.1109/ssci52147.2023.10371868
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