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204 Publications
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
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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
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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
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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
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2023 | Journal Article | LibreCat-ID: 46310
Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2023). A study on the effects of normalized TSP features for automated algorithm selection. Theoretical Computer Science, 940, 123–145. https://doi.org/10.1016/j.tcs.2022.10.019
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2023 | Conference Paper | LibreCat-ID: 48898
Seiler, M., Rook, J., Heins, J., Preuß, O. L., Bossek, J., & Trautmann, H. (n.d.). Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 361–368. https://doi.org/10.1109/SSCI52147.2023.10372008
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2022 | Book Chapter | LibreCat-ID: 46300
Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., & Trautmann, H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In G. Weitzel & S. Mündges (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen (pp. 249–274). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-658-35658-3_13
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2022 | Conference Paper | LibreCat-ID: 46301
Assenmacher, D., & Trautmann, H. (2022). Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption. In T. et al. Tran (Ed.), Intelligent Information and Database Systems (pp. 3–16). Springer International Publishing. https://doi.org/10.1007/978-3-031-21743-2_1
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2022 | Journal Article | LibreCat-ID: 46316
Assenmacher, D., Weber, D., Preuss, M., Valdez, A. C., Bradshaw, A., Ross, B., Cresci, S., Trautmann, H., Neumann, F., & Grimme, C. (2022). Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review, 40(6), 1496–1522. https://doi.org/10.1177/08944393211012268
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2022 | Conference Paper | LibreCat-ID: 46306
Schneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H., & Kerschke, P. (2022). HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII (pp. 575–589). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_40
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2022 | Journal Article | LibreCat-ID: 46308
Aspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H., & Grimme, C. (2022). The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. Natural Computing, 1, 1–15. https://doi.org/10.1007/s11047-022-09919-w
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2022 | Conference Paper | LibreCat-ID: 48861
Bossek, J., & Neumann, F. (2022). Exploring the Feature Space of TSP Instances Using Quality Diversity. Proceedings of the Genetic and Evolutionary Computation Conference, 186–194. https://doi.org/10.1145/3512290.3528851
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2022 | Conference Paper | LibreCat-ID: 48868
Bossek, J., Neumann, A., & Neumann, F. (2022). Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 824–842. https://doi.org/10.1145/3520304.3533626
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2022 | Conference Paper | LibreCat-ID: 48882
Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., & Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 192–206). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_14
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2022 | Conference Paper | LibreCat-ID: 48894
Nikfarjam, A., Neumann, A., Bossek, J., & Neumann, F. (2022). Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tu\v sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 237–249). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_17
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2022 | Journal Article | LibreCat-ID: 48878
Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022). Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences, 12(18), 9094. https://doi.org/10.3390/app12189094
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2022 | Conference Paper | LibreCat-ID: 48896
Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. https://doi.org/10.1145/3520304.3528998
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2022 | Journal Article | LibreCat-ID: 52532
Rodrigues, A. S., Kerschke, P., Pereira, C. A. D. B., Trautmann, H., Wagner, C., Hellingrath, B., & Polpo, A. (2022). Estimation of component reliability from superposed renewal processes by means of latent variables. Comput. Stat., 37(1), 355–379. https://doi.org/10.1007/S00180-021-01124-0
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2022 | Conference Paper | LibreCat-ID: 46307
Seiler, M., Prager, R. P., Kerschke, P., & Trautmann, H. (2022). A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes. Proceedings of the Genetic and Evolutionary Computation Conference, 657–665. https://doi.org/10.1145/3512290.3528834
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