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143 Publications
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.
LibreCat
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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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2022 | Conference Paper | LibreCat-ID: 46304
R. P. Prager, M. 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. 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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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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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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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.
LibreCat
2021 | Journal Article | LibreCat-ID: 46318
C. Grimme et al., “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” Computers & Operations Research, vol. 136, p. 105489, 2021, doi: https://doi.org/10.1016/j.cor.2021.105489.
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2021 | Conference Paper | LibreCat-ID: 46311
P. Aspar, P. Kerschke, V. Steinhoff, H. Trautmann, and C. Grimme, “Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization,” in Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings, 2021, pp. 311–322, doi: 10.1007/978-3-030-72062-9_25.
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2021 | Journal Article | LibreCat-ID: 46317
C. Coombs et al., “What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective,” International Journal of Information Management, vol. 58, 2021, doi: 10.1016/j.ijinfomgt.2021.102311.
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2021 | Conference Paper | LibreCat-ID: 46315
R. P. Prager, M. Seiler, H. Trautmann, and P. Kerschke, “Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization,” in 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021, pp. 1–8, doi: 10.1109/SSCI50451.2021.9660174.
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2021 | Conference Paper | LibreCat-ID: 46312
D. Assenmacher, M. Niemann, K. Müller, M. Seiler, D. M. Riehle, and H. Trautmann, “RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets,” in Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), 2021, pp. 1–14.
LibreCat
2021 | Conference Paper | LibreCat-ID: 46313
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “On the Potential of Normalized TSP Features for Automated Algorithm Selection,” in Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of genetic Algorithms (FOGA XVI), 2021, pp. 1–15, doi: 10.1145/3450218.3477308.
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