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213 Publications
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
| DOI
2022 | Conference Paper | LibreCat-ID: 48861
J. Bossek and F. Neumann, “Exploring the Feature Space of TSP Instances Using Quality Diversity,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2022, pp. 186–194, doi: 10.1145/3512290.3528851.
LibreCat
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2022 | Conference Paper | LibreCat-ID: 48868
J. Bossek, A. Neumann, and F. Neumann, “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 824–842, doi: 10.1145/3520304.3533626.
LibreCat
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2022 | Conference Paper | LibreCat-ID: 48882
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, doi: 10.1007/978-3-031-14714-2_14.
LibreCat
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2022 | Conference Paper | LibreCat-ID: 48894
A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.
LibreCat
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2022 | Journal Article | LibreCat-ID: 48878
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. 18, p. 9094, 2022, doi: 10.3390/app12189094.
LibreCat
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2022 | Conference Paper | LibreCat-ID: 48896
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, doi: 10.1145/3520304.3528998.
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.
LibreCat
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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.
LibreCat
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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.
LibreCat
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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.
LibreCat
| 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.
LibreCat
| 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.
LibreCat
| DOI
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.
LibreCat
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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.
LibreCat
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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.
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48853
J. Bossek, A. Neumann, and F. Neumann, “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 556–564, doi: 10.1145/3449639.3459364.
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48855
J. Bossek, A. Neumann, and F. Neumann, “Exact Counting and~Sampling of Optima for the Knapsack Problem,” in Learning and Intelligent Optimization, 2021, pp. 40–54, doi: 10.1007/978-3-030-92121-7_4.
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48860
J. Bossek and F. Neumann, “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 198–206, doi: 10.1145/3449639.3459363.
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