Heike Trautmann

Fakultät für Elektrotechnik, Informatik und Mathematik
htrautm@mail.uni-paderborn.de
ID
100740

130 Publications

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[130]
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
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[129]
2024 | Conference Paper | LibreCat-ID: 52749
Vinzent 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
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[128]
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
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[127]
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
 
[126]
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
 
[125]
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
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[124]
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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[123]
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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[122]
2023 | Conference Paper | LibreCat-ID: 48898
Seiler, M. V., 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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[121]
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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[120]
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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[119]
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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[118]
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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[117]
2022 | Conference Paper | LibreCat-ID: 46307
Seiler, M. V., 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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[116]
2022 | Conference Paper | LibreCat-ID: 46304
Prager, R. P., Seiler, M. V., Trautmann, H., & Kerschke, P. (2022). Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII (pp. 3–17). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_1
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[115]
2022 | Conference Paper | LibreCat-ID: 46303
Pohl, J. S., Assenmacher, D., Seiler, M. V., Trautmann, H., & Grimme, C. (2022). Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM) (pp. 1–10). AAAI Press. https://doi.org/10.36190/2022.91
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[114]
2022 | Conference Paper | LibreCat-ID: 46305
Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In J. Fieldsend & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 356–359–356–359). Association for Computing Machinery. https://doi.org/10.1145/3520304.3528998
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[113]
2022 | Journal Article | LibreCat-ID: 46309
Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022). Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences, 12(8), 1–44. https://doi.org/10.3390/app12189094
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[112]
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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[111]
2022 | Conference Paper | LibreCat-ID: 46302
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. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII (pp. 192–206). Springer International Publishing.
LibreCat
 
[110]
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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[109]
2021 | Journal Article | LibreCat-ID: 46318
Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., & Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research, 136, 105489. https://doi.org/10.1016/j.cor.2021.105489
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[108]
2021 | Conference Paper | LibreCat-ID: 46313
Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. In for Computing Machinery Association (Ed.), Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of genetic Algorithms (FOGA XVI) (pp. 1–15). Association for Computing Machinery. https://doi.org/10.1145/3450218.3477308
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[107]
2021 | Conference Paper | LibreCat-ID: 46311
Aspar, P., Kerschke, P., Steinhoff, V., Trautmann, H., & Grimme, C. (2021). Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization. In H. et al. Ishibuchi (Ed.), Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings (pp. 311–322). Springer. https://doi.org/10.1007/978-3-030-72062-9_25
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[106]
2021 | Journal Article | LibreCat-ID: 46317
Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., Carvalho, J. Á., Fantinato, M., Garmann-Johnsen, N. F., Grimme, C., Stein, A., & Trautmann, H. (2021). What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective. International Journal of Information Management, 58. https://doi.org/10.1016/j.ijinfomgt.2021.102311
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[105]
2021 | Conference Paper | LibreCat-ID: 46315
Prager, R. P., Vinzent Seiler, M., Trautmann, H., & Kerschke, P. (2021). Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization. 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8. https://doi.org/10.1109/SSCI50451.2021.9660174
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[104]
2021 | Conference Paper | LibreCat-ID: 46312
Assenmacher, D., Niemann, M., Müller, K., Seiler, M. V., Riehle, D. M., & Trautmann, H. (2021). RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets. Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), 1–14.
LibreCat
 
[103]
2020 | Conference Paper | LibreCat-ID: 46319
Assenmacher, D., Adam, L., Trautmann, H., & Grimme, C. (2020). Towards Real-Time and Unsupervised Campaign Detection in Social Media. Proceedings of the Florida Artificial Intelligence Research Society Conference.
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[102]
2020 | Conference Paper | LibreCat-ID: 46328
Prager, R. P., Trautmann, H., Wang, H., Bäck, T. H. W., & Kerschke, P. (2020). Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 996–1003. https://doi.org/10.1109/SSCI47803.2020.9308510
LibreCat | DOI
 
[101]
2020 | Conference Paper | LibreCat-ID: 46320
Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020). A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In G. Meiselwitz (Ed.), Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (pp. 201–214). Springer International Publishing. https://doi.org/10.1007/978-3-030-49570-1_14
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[100]
2020 | Conference Paper | LibreCat-ID: 46325
Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). Towards Automated Configuration of Stream Clustering Algorithms. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19), 137–143. https://doi.org/10.1007/978-3-030-43823-4_12
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[99]
2020 | Conference Paper | LibreCat-ID: 46321
Assenmacher, D., Frischlich , L., Trautmann, H., Grimme, C., & Adam, L. (2020). Inside the tool set of automation: Free social bot code revisited. In C. Grimme, M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in open online media (pp. 101–114). Springer.
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[98]
2020 | Conference Paper | LibreCat-ID: 46326
Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020), 80–95. https://doi.org/10.1007/978-3-030-53552-0_10
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[97]
2020 | Conference Paper | LibreCat-ID: 46324
Bossek, J., Kerschke, P., & Trautmann, H. (2020). Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8.
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[96]
2020 | Conference Paper | LibreCat-ID: 46322
Bossek, J., Grimme, C., Rudolph, G., & Trautmann, H. (2020). Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8. https://doi.org/10.1109/CEC48606.2020.9185778
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[95]
2020 | Conference Paper | LibreCat-ID: 46323
Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 166–174.
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[94]
2020 | Conference Paper | LibreCat-ID: 46327
Lena, C., Frischlich, L., Trautmann, H., & Grimme, C. (2020). Automated detection of nostalgic text in the context of societal pessimism. In C. Grimme, M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in open online media (pp. 48–58).
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[93]
2020 | Conference Paper | LibreCat-ID: 46330
Seiler, M. V., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, & H. Trautmann (Eds.), Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI) (pp. 48–64). https://doi.org/10.1007/978-3-030-58112-1_4
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[92]
2020 | Conference Paper | LibreCat-ID: 46329
Riehle, D. M., Niemann, M., Brunk, J., Assenmacher, D., Trautmann, H., & Becker, J. (2020). Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation Tool. In G. Meiselwitz (Ed.), Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing (pp. 71–86). Springer International Publishing.
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[91]
2020 | Journal Article | LibreCat-ID: 46333
Assenmacher, D., Clever, L., Frischlich, L., Quandt, T., Trautmann, H., & Grimme, C. (2020). Demystifying Social Bots: On the Intelligence of Automated Social Media Actors. Social Media + Society, 6(3), 2056305120939264. https://doi.org/10.1177/2056305120939264
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[90]
2020 | Journal Article | LibreCat-ID: 46334
Bossek, J., Kerschke, P., & Trautmann, H. (2020). A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Applied Soft Computing, 88, 105901. https://doi.org/10.1016/j.asoc.2019.105901
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[89]
2020 | Conference Paper | LibreCat-ID: 46331
Seiler, M. V., Trautmann, H., & Kerschke, P. (2020). Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries. Proceedings of the International Joint Conference on Neural Networks (IJCNN), 1–8. https://doi.org/10.1109/IJCNN48605.2020.9207338
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[88]
2020 | Conference Paper | LibreCat-ID: 46332
Steinhoff, V., Kerschke, P., Aspar, P., Trautmann, H., & Grimme, C. (2020). Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 2445–2452. https://doi.org/10.1109/SSCI47803.2020.9308259
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[87]
2019 | Conference Paper | LibreCat-ID: 46338
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 516–528). Springer International Publishing. https://doi.org/10.1007/978-3-030-12598-1_41
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[86]
2019 | Conference Paper | LibreCat-ID: 46343
Grimme, C., Kerschke, P., & Trautmann, H. (2019). Multimodality in Multi-Objective Optimization — More Boon than Bane? In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 126–138). Springer. https://doi.org/10.1007/978-3-030-12598-1_11
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[85]
2019 | Journal Article | LibreCat-ID: 46345
Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated Algorithm Selection: Survey and Perspectives. Evolutionary Computation (ECJ), 27(1), 3–45. https://doi.org/10.1162/evco_a_00242
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[84]
2019 | Conference Paper | LibreCat-ID: 46339
Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. In T. Friedrich, C. Doerr, & D. Arnold (Eds.), Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV) (pp. 58–71). https://doi.org/10.1145/3299904.3340307
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[83]
2019 | Conference Paper | LibreCat-ID: 46337
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. Pardalos (Eds.), Learning and Intelligent Optimization (Vol. 11353, pp. 215–219). Springer.
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[82]
2019 | Journal Article | LibreCat-ID: 46344
Carnein, M., & Trautmann, H. (2019). Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms. Business and Information Systems Engineering (BISE), 61(3), 277–297.
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[81]
2019 | Conference Paper | LibreCat-ID: 46340
Carnein, M., Homann, L., Trautmann, H., & Vossen, G. (2019). A Recommender System Based on Omni-Channel Customer Data. Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 65–74.
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[80]
2019 | Conference Paper | LibreCat-ID: 46341
Carnein, M., & Trautmann, H. (2019). Customer Segmentation Based on Transactional Data Using Stream Clustering. Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), 280–292.
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[79]
2019 | Conference Paper | LibreCat-ID: 46342
Grimme, C., Kerschke, P., Emmerich, M. T. M., Preuss, M., Deutz, A. H., & Trautmann, H. (2019). Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization. AIP Conference Proceedings, 020052-1-020052–020054. https://doi.org/10.1063/1.5090019
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[78]
2019 | Book Chapter | LibreCat-ID: 46336
Kerschke, P., & Trautmann, H. (2019). Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-package flacco. In N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, & M. Vichi (Eds.), Applications in Statistical Computing (pp. 93–123). Springer. https://doi.org/10.1007/978-3-030-25147-5_7
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[77]
2019 | Book | LibreCat-ID: 46335
Trautmann, H. (2019). Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement. Springer International Publishing.
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[76]
2019 | Journal Article | LibreCat-ID: 46346
Kerschke, P., & Trautmann, H. (2019). Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning. Evolutionary Computation (ECJ), 27(1), 99–127. https://doi.org/10.1162/evco_a_00236
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[75]
2019 | Journal Article | LibreCat-ID: 46347
Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2019). Search Dynamics on Multimodal Multi-Objective Problems. Evolutionary Computation (ECJ), 27(4), 577–609. https://doi.org/10.1162/evco_a_00234
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[74]
2018 | Conference Paper | LibreCat-ID: 46350
van Engelen, J. E., van Lier, J. J., Takes, F. W., & Trautmann, H. (2018). Accurate WiFi based indoor positioning with continuous location sampling. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), 524–540.
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[73]
2018 | Conference Paper | LibreCat-ID: 46348
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
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[72]
2018 | Journal Article | LibreCat-ID: 46351
Carnein, M., & Trautmann, H. (2018). evoStream — Evolutionary Stream Clustering Utilizing Idle Times. Big Data Research, 14, 101–111. https://doi.org/10.1016/j.bdr.2018.05.005
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[71]
2018 | Journal Article | LibreCat-ID: 46353
Li, L., Wang, Y., Trautmann, H., Jing, N., & Emmerich, M. (2018). Multiobjective evolutionary algorithms based on target region preferences. Swarm and Evolutionary Computation, 40, 196–215. https://doi.org/10.1016/j.swevo.2018.02.006
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[70]
2018 | Journal Article | LibreCat-ID: 46352
Kerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H., & Trautmann, H. (2018). Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation (ECJ), 26(4), 597–620. https://doi.org/10.1162/evco_a_00215
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[69]
2018 | Conference Paper | LibreCat-ID: 46349
Kerschke, P., Bossek, J., & Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’18) Companion, 1737–1744. https://doi.org/10.1145/3205651.3208233
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[68]
2017 | Book Chapter | LibreCat-ID: 46355
Adrián, S. H. V., Lara, A., Trautmann, H., Rudolph, G., & Schütze, O. (2017). The Directed Search Method for Unconstrained Parameter Dependent Multi-objective Optimization Problems. In O. Schütze, L. Trujillo, P. Legrand, & Y. Maldonado (Eds.), NEO 15 (pp. 281–330). Springer International Publishing. https://doi.org/10.1007/978-3-319-44003-3_12
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[67]
2017 | Conference Paper | LibreCat-ID: 46360
Carnein, M., Heuchert, M., Homann, L., Trautmann, H., Vossen, G., Becker, J., & Kraume, K. (2017). Towards Efficient and Informative Omni-Channel Customer Relationship Management. In S. de Cesare & F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17) (Vol. 10651, pp. 69–78). Springer International Publishing. https://doi.org/10.1007/978-3-319-70625-2_7
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[66]
2017 | Conference Paper | LibreCat-ID: 46361
Carnein, M., Homann, L., Trautmann, H., Vossen, G., & Kraume, K. (2017). Customer Service in Social Media — An Empirical Study of the Airline Industry. In N. Ritter, H. Schwarz, M. Klettke, A. Thor, O. Kopp, & M. W. Bernhard (Eds.), Proceedings of the 17$^th$ Conference on Database Systems for Business, Technology, and Web (BTW ’17): Vol. P-266 (pp. 33–40). Gesellschaft für Informatik.
LibreCat
 
[65]
2017 | Book Chapter | LibreCat-ID: 46356
Li, L., Yevseyeva, I., Basto-Fernandes, V., Trautmann, H., Jing, N., & Emmerich, M. (2017). Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, & C. Grimme (Eds.), Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 406–421). Springer International Publishing. https://doi.org/10.1007/978-3-319-54157-0_28
LibreCat | DOI
 
[64]
2017 | Book Chapter | LibreCat-ID: 46357
Tierney, K., Handali, J., Grimme, C., & Trautmann, H. (2017). Multi-objective Optimization for Liner Shipping Fleet Repositioning. In H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, & C. Grimme (Eds.), Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 622–638). Springer International Publishing. https://doi.org/10.1007/978-3-319-54157-0_42
LibreCat | DOI
 
[63]
2017 | Conference Paper | LibreCat-ID: 46359
Carnein, M., Assenmacher, D., & Trautmann, H. (2017). Stream Clustering of Chat Messages with Applications to Twitch Streams. In S. de Cesare & F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17) (pp. 79–88). Springer International Publishing. https://doi.org/10.1007/978-3-319-70625-2_8
LibreCat | DOI
 
[62]
2017 | Journal Article | LibreCat-ID: 46362
Grimme, C., Preuss, M., Adam, L., & Trautmann, H. (2017). Social Bots: Human-Like by Means of Human Control? Big Data, 5(4), 279–293. https://doi.org/10.1089/big.2017.0044
LibreCat | DOI
 
[61]
2017 | Conference Paper | LibreCat-ID: 46358
Carnein, M., Assenmacher, D., & Trautmann, H. (2017). An Empirical Comparison of Stream Clustering Algorithms. Proceedings of the ACM International Conference on Computing Frontiers (CF ’17), 361–365. https://doi.org/10.1145/3075564.3078887
LibreCat | DOI
 
[60]
2016 | Conference Paper | LibreCat-ID: 46364
Blot, A., Hoos, H., Jourdan, L., Marmion, M., & Trautmann, H. (2016). MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In V. et al. Joaquin (Ed.), LION 2016: Learning and Intelligent Optimization (Vol. 10079, pp. 32–47). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_3
LibreCat | DOI
 
[59]
2016 | Book Chapter | LibreCat-ID: 46363
Rudolph, G., Schütze, O., & Trautmann, H. (2016). On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. In G. Squillero & P. Burelli (Eds.), Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II (pp. 42–55). Springer International Publishing. https://doi.org/10.1007/978-3-319-31153-1_4
LibreCat | DOI
 
[58]
2016 | Conference Paper | LibreCat-ID: 46365
Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization (Vol. 10079, pp. 48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
LibreCat | DOI
 
[57]
2016 | Conference Paper | LibreCat-ID: 46366
Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In G. Adorni, S. Cagnoni, M. Gori, & M. Maratea (Eds.), AI*IA 2016 Advances in Artificial Intelligence (Vol. 10037, pp. 3–12). Springer. https://doi.org/10.1007/978-3-319-49130-1_1
LibreCat | DOI
 
[56]
2016 | Conference Paper | LibreCat-ID: 46369
Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2016). Towards Analyzing Multimodality of Multiobjective Landscapes. Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV), 962–972. https://doi.org/10.1007/978-3-319-45823-6_90
LibreCat | DOI
 
[55]
2016 | Conference Paper | LibreCat-ID: 46367
Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236. https://doi.org/10.1145/2908812.2908845
LibreCat | DOI
 
[54]
2016 | Journal Article | LibreCat-ID: 46371
Rudolph, G., Schütze, O., Grimme, C., Domínguez-Medina, C., & Trautmann, H. (2016). Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results. Computational Optimization and Applications (Comput. Optim. Appl.), 64(2), 589–618. https://doi.org/10.1007/s10589-015-9815-8
LibreCat | DOI
 
[53]
2016 | Journal Article | LibreCat-ID: 46372
Schütze, O., Sosa, H. V., Trautmann, H., & Rudolph, G. (2016). The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. Journal of Heuristics, 22(3), 273–300. https://doi.org/10.1007/s10732-016-9310-0
LibreCat | DOI
 
[52]
2016 | Conference Paper | LibreCat-ID: 46368
Kerschke, P., & Trautmann, H. (2016). The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems. Proceedings of the IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2016.7748359
LibreCat | DOI
 
[51]
2016 | Journal Article | LibreCat-ID: 46370
Neumann, F., & Trautmann, H. (2016). Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). Dagstuhl Reports, 5(5), 78–79. https://doi.org/10.4230/DagRep.5.5.57
LibreCat | DOI
 
[50]
2015 | Conference Paper | LibreCat-ID: 46373
Chinnov, A., Kerschke, P., Meske, C., Stieglitz, S., & Trautmann, H. (2015). An Overview of Topic Discovery in Twitter Communication through Social Media Analytics. Proceedings of the 20$^th$ Americas Conference on Information Systems (AMCIS ’15), 1–10.
LibreCat
 
[49]
2015 | Conference Paper | LibreCat-ID: 46375
Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2015). Detecting Funnel Structures by Means of Exploratory Landscape Analysis. In S. Silva (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15) (pp. 265–272). ACM. https://doi.org/10.1145/2739480.2754642
LibreCat | DOI
 
[48]
2015 | Conference Paper | LibreCat-ID: 46377
Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15), 425–432. https://doi.org/10.1145/2739480.2754705
LibreCat | DOI
 
[47]
2015 | Conference Paper | LibreCat-ID: 46376
Kotthoff, L., Kerschke, P., Hoos, H., & Trautmann, H. (2015). Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection. In C. Dhaenens, L. Jourdan, & M.-E. Marmion (Eds.), Learning and Intelligent Optimization (pp. 202–217). Springer International Publishing.
LibreCat
 
[46]
2015 | Journal Article | LibreCat-ID: 46379
Brockhoff, D., Wagner, T., & Trautmann, H. (2015). R2 Indicator Based Multiobjective Search. Evolutionary Computation Journal, 23(3), 369–395. https://doi.org/10.1162/EVCO_a_00135
LibreCat | DOI
 
[45]
2015 | Conference Paper | LibreCat-ID: 46374
Grimme, C., Meisel, S., Trautmann, H., Rudolph, G., & Wölck, M. (2015). Multi-Objective Analysis of Approaches to Dynamic Routing Of a Vehicle. Proceedings of the European Conference On Information Systems.
LibreCat
 
[44]
2015 | Journal Article | LibreCat-ID: 46380
Mersmann, O., Preuss, M., Trautmann, H., Bischl, B., & Weihs, C. (2015). Analyzing the BBOB Results by Means of Benchmarking Concepts. Evolutionary Computation Journal, 23(1), 161–185.
LibreCat
 
[43]
2014 | Book Chapter | LibreCat-ID: 46381
Kerschke, P., Preuss, M., Hernández, C., Schütze, O., Sun, J.-Q., Grimme, C., Rudolph, G., Bischl, B., & Trautmann, H. (2014). Cell Mapping Techniques for Exploratory Landscape Analysis. In A.-A. Tantar, E. Tantar, J.-Q. Sun, W. Zhang, Q. Ding, O. Schütze, M. T. M. Emmerich, P. Legrand, M. P. Del, & C. C. A. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 115–131). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_9
LibreCat | DOI
 
[42]
2014 | Book Chapter | LibreCat-ID: 46382
Rudolph, G., Schütze, O., Grimme, C., & Trautmann, H. (2014). A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets. In A. Tantar, E. Tantar, J. Sun, W. Zhang, Q. Ding, O. Schütze, M. Emmerich, P. Legrand, M. P. Del, & C. C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 261–273). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_18
LibreCat | DOI
 
[41]
2014 | Conference Paper | LibreCat-ID: 46383
Rudolph, G., Grimme, C., Schütze, O., & Trautmann, H. (2014). An Aspiration Set EMOA Based on Averaged Hausdorff Distances. Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), 8426, 153–156.
LibreCat
 
[40]
2014 | Conference Paper | LibreCat-ID: 46384
Wessing, S., Preuss, M., & Trautmann, H. (2014). Stopping Criteria for Multimodal Optimization. In T. Bartz-Beielstein, J. Branke, B. Filipic, & J. Smith (Eds.), Proceedings of the Parallel Problem Solving from Nature — PPSN XIII (Vol. 8672, pp. 141–150). Springer. https://doi.org/10.1007/978-3-319-10762-2_14
LibreCat | DOI
 
[39]
2013 | Book Chapter | LibreCat-ID: 46385
Sosa, H. V., Schütze, O., Rudolph, G., & Trautmann, H. (2013). The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. In M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, & C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV (Vol. 227, pp. 189–205). Springer International Publishing. https://doi.org/10.1007/978-3-319-01128-8_13
LibreCat | DOI
 
[38]
2013 | Book Chapter | LibreCat-ID: 46386
Trautmann, H., Rudolph, G., Dominguez-Medina, C., & Schütze, O. (2013). Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems. In O. Schütze, C. C. Coello, A. Tantar, E. Tantar, P. Bouvry, M. P. Del, & P. Legrand (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (Vol. 175, pp. 89–105). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_6
LibreCat | DOI
 
[37]
2013 | Conference Paper | LibreCat-ID: 46388
Nallaperuma, S., Wagner, M., Neumann, F., Bischl, B., Mersmann, O., & Trautmann, H. (2013). A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem. Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII, 147–160. https://doi.org/10.1145/2460239.2460253
LibreCat | DOI
 
[36]
2013 | Conference Paper | LibreCat-ID: 46390
Rudolph, G., Trautmann, H., Sengupta, S., & Schütze, O. (2013). Evenly Spaced Pareto Front Approximations for Tricriteria Problems Based on Triangulation. In R. Purshouse, P. Fleming, C. Fonseca, S. Greco, & J. Shaw (Eds.), Evolutionary Multi-Criterion Optimization — 7$^th$ International Conference, EMO 2013, Sheffield, UK, Proceedings (Vol. 7811, pp. 443–458). Springer. https://doi.org/10.1007/978-3-642-37140-0_34
LibreCat | DOI
 
[35]
2013 | Conference Paper | LibreCat-ID: 46391
Sosa-Hernandez, V., Schütze, O., Rudoph, G., & Trautmann, H. (2013). Directed Search Method for Indicator-based Multi-objective Evolutionary Algorithms. Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion, 1699–1702. https://doi.org/10.1145/2464576.2482756
LibreCat | DOI
 
[34]
2013 | Conference Paper | LibreCat-ID: 46387
Dominguez-Medina, C., Rudolph, G., Schütze, O., & Trautmann, H. (2013). Evenly spaced Pareto fronts of quad-objective problems using PSA partitioning technique. Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC), 3190–3197. https://doi.org/10.1109/CEC.2013.6557960
LibreCat | DOI
 
[33]
2013 | Conference Paper | LibreCat-ID: 46389
Preuss, M., Kozakowski, D., Hagelbäck, J., & Trautmann, H. (2013). Reactive strategy choice in StarCraft by means of Fuzzy Control. 2013 IEEE Conference on Computational Inteligence in Games (CIG), 1–8. https://doi.org/10.1109/CIG.2013.6633627
LibreCat | DOI
 
[32]
2013 | Journal Article | LibreCat-ID: 46395
Trautmann, H., Wagner, T., Biermann, D., & Weihs, C. (2013). Indicator-based Selection in Evolutionary Multiobjective Optimization Algorithms Based On the Desirability Index. Journal of Multi-Criteria Decision Analysis, 20(5–6), 319–337. https://doi.org/10.1002/mcda.1503
LibreCat | DOI
 
[31]
2013 | Conference Paper | LibreCat-ID: 46393
Wagner, T., Trautmann, H., & Brockhoff, D. (2013). Preference Articulation by Means of the R2 Indicator. In R. C. Purshouse, P. J. Fleming, C. M. Fonseca, S. Greco, & J. Shaw (Eds.), Evolutionary Multi-Criterion Optimization (pp. 81–95). Springer Berlin Heidelberg.
LibreCat
 
[30]
2013 | Conference Paper | LibreCat-ID: 46392
Trautmann, H., Wagner, T., & Brockhoff, D. (2013). R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. In G. Nicosia & P. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 70–74). Springer Berlin Heidelberg.
LibreCat
 
[29]
2013 | Journal Article | LibreCat-ID: 46394
Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. Annals of Mathematics and Artificial Intelligence, 69, 151–182.
LibreCat
 
[28]
2012 | Conference Paper | LibreCat-ID: 46397
Brockhoff, D., Wagner, T., & Trautmann, H. (2012). On the Properties of the R2 Indicator. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, 465–472. https://doi.org/10.1145/2330163.2330230
LibreCat | DOI
 
[27]
2012 | Conference Paper | LibreCat-ID: 46396
Bischl, B., Mersmann, O., Trautmann, H., & Preuß, M. (2012). Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, 313–320. https://doi.org/10.1145/2330163.2330209
LibreCat | DOI
 
[26]
2012 | Conference Paper | LibreCat-ID: 46398
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. In Y. Hamadi & M. Schoenauer (Eds.), Learning and Intelligent Optimization (pp. 115–129). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_9
LibreCat | DOI
 
[25]
2012 | Journal Article | LibreCat-ID: 46399
Bischl, B., Mersmann, O., Trautmann, H., & Weihs, C. (2012). Resampling Methods in Model Validation. Evolutionary Computation Journal, 20(2), 249–275. https://doi.org/10.1162/EVCO_a_00069
LibreCat | DOI
 
[24]
2012 | Journal Article | LibreCat-ID: 46400
Rudolph, G., Trautmann, H., & Schütze, O. (2012). Homogene Approximation der Paretofront bei mehrkriteriellen Kontrollproblemen. At-Automatisierungstechnik, 60, 610–621. https://doi.org/10.1524/auto.2012.1033
LibreCat | DOI
 
[23]
2011 | Conference Paper | LibreCat-ID: 46401
Mersmann, O., Bischl, B., Trautmann, H., Preuss, M., Weihs, C., & Rudolph, G. (2011). Exploratory Landscape Analysis. Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, 829–836. https://doi.org/10.1145/2001576.2001690
LibreCat | DOI
 
[22]
2011 | Conference Paper | LibreCat-ID: 46402
Wagner, T., Trautmann, H., & Martí, L. (2011). A Taxonomy of Online Stopping Criteria for Multi-Objective Evolutionary Algorithms. In R. H. C. Takahashi, K. Deb, E. F. Wanner, & S. Greco (Eds.), Evolutionary Multi-Criterion Optimization (pp. 16–30). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_2
LibreCat | DOI
 
[21]
2011 | Journal Article | LibreCat-ID: 46403
Naujoks, B., Trautmann, H., Wessing, S., & Weihs, C. (2011). Advanced concepts for multi-objective evolutionary optimization in aircraft industry. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 225(10), 1081–1096. https://doi.org/10.1177/0954410011414120
LibreCat | DOI
 
[20]
2010 | Conference Paper | LibreCat-ID: 46408
Mostaghim, S., Trautmann, H., & Mersmann, O. (2010). Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 101–110). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_11
LibreCat | DOI
 
[19]
2010 | Conference Paper | LibreCat-ID: 46405
Mersmann, O., Preuss, M., & Trautmann, H. (2010). Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I, 73–82.
LibreCat
 
[18]
2010 | Conference Paper | LibreCat-ID: 46406
Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). On the Distribution of EMOA Hypervolumes. In C. Blum & R. Battiti (Eds.), Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy (Vol. 6073, pp. 333–337). Springer.
LibreCat
 
[17]
2010 | Conference Paper | LibreCat-ID: 46407
Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). Benchmarking evolutionary multiobjective optimization algorithms. IEEE Congress on Evolutionary Computation, 1–8. https://doi.org/10.1109/CEC.2010.5586241
LibreCat | DOI
 
[16]
2010 | Conference Paper | LibreCat-ID: 46404
Ding, J., Wessing, S., Trautmann, H., Mehnen, J., & Naujoks, B. (2010). Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing. In R. Teti (Ed.), Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10). Copyright C.O.C. Com. org. Conv.
LibreCat
 
[15]
2010 | Conference Paper | LibreCat-ID: 46409
Voß, T., Trautmann, H., & Igel, C. (2010). New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 260–269). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_27
LibreCat | DOI
 
[14]
2010 | Journal Article | LibreCat-ID: 46412
Wagner, T., & Trautmann, H. (2010). Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions. IEEE Transactions on Evolutionary Computation, 14(5), 688–701. https://doi.org/10.1109/TEVC.2010.2058119
LibreCat | DOI
 
[13]
2010 | Journal Article | LibreCat-ID: 46411
Azene, Y. T., Roy, R., Farrugia, D., Onisa, C., Mehnen, J., & Trautmann, H. (2010). Work roll cooling system design optimisation in presence of uncertainty and constrains. CIRP Journal of Manufacturing Science and Technology, 2(4), 290–298. https://doi.org/10.1016/j.cirpj.2010.06.001
LibreCat | DOI
 
[12]
2010 | Conference Paper | LibreCat-ID: 46410
Wagner, T., & Trautmann, H. (2010). Online convergence detection for evolutionary multi-objective algorithms revisited. IEEE Congress on Evolutionary Computation, 1–8. https://doi.org/10.1109/CEC.2010.5586474
LibreCat | DOI
 
[11]
2009 | Conference Paper | LibreCat-ID: 46414
Wagner, T., Trautmann, H., & Naujoks, B. (2009). OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing. In M. Ehrgott, C. M. Fonseca, X. Gandibleux, J.-K. Hao, & M. Sevaux (Eds.), Evolutionary Multi-Criterion Optimization (pp. 198–215). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-01020-0_19
LibreCat | DOI
 
[10]
2009 | Conference Paper | LibreCat-ID: 46415
Trautmann, H., Mehnen, J., & Naujoks, B. (2009). Pareto-dominance in noisy environments. 2009 IEEE Congress on Evolutionary Computation, 3119–3126. https://doi.org/10.1109/CEC.2009.4983338
LibreCat | DOI
 
[9]
2009 | Conference Paper | LibreCat-ID: 46413
Naujoks, B., & Trautmann, H. (2009). Online convergence detection for multiobjective aerodynamic applications. 2009 IEEE Congress on Evolutionary Computation, 332–339. https://doi.org/10.1109/CEC.2009.4982966
LibreCat | DOI
 
[8]
2009 | Journal Article | LibreCat-ID: 46416
Trautmann, H., & Mehnen, J. (2009). Statistical Methods for Improving Multi-objective Evolutionary Optimisation. International Journal of Computational Intelligence Research, 5(2), 72–78.
LibreCat
 
[7]
2009 | Journal Article | LibreCat-ID: 46418
Trautmann, H., Wagner, T., Naujoks, B., Preuss, M., & Mehnen, J. (2009). Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms. Evolutionary Computation, 17(4), 493–509. https://doi.org/10.1162/evco.2009.17.4.17403
LibreCat | DOI
 
[6]
2009 | Journal Article | LibreCat-ID: 46417
Trautmann, H., & Mehnen, J. (2009). Preference-based Pareto optimization in certain and noisy environments. Engineering Optimization, 41(1), 23–38. https://doi.org/10.1080/03052150802347926
LibreCat | DOI
 
[5]
2008 | Conference Paper | LibreCat-ID: 46420
Trautmann, H., Ligges, U., Mehnen, J., & Preuss, M. (2008). A Convergence Criterion for Multiobjective Evolutionary Algorithms Based on Systematic Statistical Testing. In G. Rudolph, T. Jansen, N. Beume, S. Lucas, & C. Poloni (Eds.), Parallel Problem Solving from Nature – PPSN X (pp. 825–836). Springer Berlin Heidelberg.
LibreCat
 
[4]
2008 | Conference Paper | LibreCat-ID: 46419
Mehnen, J., & Trautmann, H. (2008). Robust Multi-objective Optimisation of Weld Bead Geometry for Additive Manufacturing. In R. Teti (Ed.), Proceedings of the 6$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’08). Copyright C.O.C. Com. org. Conv.
LibreCat
 
[3]
2007 | Conference Paper | LibreCat-ID: 46421
Mehnen, J., Trautmann, H., & Tiwari, A. (2007). Introducing user preference using Desirability Functions in Multi-Objective Evolutionary Optimisation of noisy processes. 2007 IEEE Congress on Evolutionary Computation, 2687–2694. https://doi.org/10.1109/CEC.2007.4424810
LibreCat | DOI
 
[2]
2006 | Journal Article | LibreCat-ID: 46423
Trautmann, H., & Weihs, C. (2006). On the Distribution of the Desirability Index using Harrington’s Desirability Function. Metrika, 63(2), 207–213. https://doi.org/10.1007/s00184-005-0012-0
LibreCat | DOI
 
[1]
2006 | Conference Paper | LibreCat-ID: 46422
Mehnen, J., & Trautmann, H. (2006). Integration of Expert’s Preferences in Pareto Optimization by Desirability Function Techniques. In R. Teti (Ed.), CIRP ICME ’06) — Proceedings of the 5$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (pp. 293–298). C.O.C. Com. org. Conv. CIRP ICME ’06.
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[130]
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
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[129]
2024 | Conference Paper | LibreCat-ID: 52749
Vinzent 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
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[128]
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
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[127]
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.
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[126]
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.
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[125]
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
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[124]
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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[123]
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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[122]
2023 | Conference Paper | LibreCat-ID: 48898
Seiler, M. V., 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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[121]
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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[120]
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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[119]
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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[118]
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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[117]
2022 | Conference Paper | LibreCat-ID: 46307
Seiler, M. V., 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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[116]
2022 | Conference Paper | LibreCat-ID: 46304
Prager, R. P., Seiler, M. V., Trautmann, H., & Kerschke, P. (2022). Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII (pp. 3–17). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_1
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[115]
2022 | Conference Paper | LibreCat-ID: 46303
Pohl, J. S., Assenmacher, D., Seiler, M. V., Trautmann, H., & Grimme, C. (2022). Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM) (pp. 1–10). AAAI Press. https://doi.org/10.36190/2022.91
LibreCat | DOI
 
[114]
2022 | Conference Paper | LibreCat-ID: 46305
Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In J. Fieldsend & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 356–359–356–359). Association for Computing Machinery. https://doi.org/10.1145/3520304.3528998
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[113]
2022 | Journal Article | LibreCat-ID: 46309
Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022). Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences, 12(8), 1–44. https://doi.org/10.3390/app12189094
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[112]
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
LibreCat | DOI
 
[111]
2022 | Conference Paper | LibreCat-ID: 46302
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. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII (pp. 192–206). Springer International Publishing.
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[110]
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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[109]
2021 | Journal Article | LibreCat-ID: 46318
Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., & Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research, 136, 105489. https://doi.org/10.1016/j.cor.2021.105489
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[108]
2021 | Conference Paper | LibreCat-ID: 46313
Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. In for Computing Machinery Association (Ed.), Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of genetic Algorithms (FOGA XVI) (pp. 1–15). Association for Computing Machinery. https://doi.org/10.1145/3450218.3477308
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[107]
2021 | Conference Paper | LibreCat-ID: 46311
Aspar, P., Kerschke, P., Steinhoff, V., Trautmann, H., & Grimme, C. (2021). Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization. In H. et al. Ishibuchi (Ed.), Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings (pp. 311–322). Springer. https://doi.org/10.1007/978-3-030-72062-9_25
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[106]
2021 | Journal Article | LibreCat-ID: 46317
Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., Carvalho, J. Á., Fantinato, M., Garmann-Johnsen, N. F., Grimme, C., Stein, A., & Trautmann, H. (2021). What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective. International Journal of Information Management, 58. https://doi.org/10.1016/j.ijinfomgt.2021.102311
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[105]
2021 | Conference Paper | LibreCat-ID: 46315
Prager, R. P., Vinzent Seiler, M., Trautmann, H., & Kerschke, P. (2021). Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization. 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8. https://doi.org/10.1109/SSCI50451.2021.9660174
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[104]
2021 | Conference Paper | LibreCat-ID: 46312
Assenmacher, D., Niemann, M., Müller, K., Seiler, M. V., Riehle, D. M., & Trautmann, H. (2021). RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets. Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), 1–14.
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[103]
2020 | Conference Paper | LibreCat-ID: 46319
Assenmacher, D., Adam, L., Trautmann, H., & Grimme, C. (2020). Towards Real-Time and Unsupervised Campaign Detection in Social Media. Proceedings of the Florida Artificial Intelligence Research Society Conference.
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[102]
2020 | Conference Paper | LibreCat-ID: 46328
Prager, R. P., Trautmann, H., Wang, H., Bäck, T. H. W., & Kerschke, P. (2020). Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 996–1003. https://doi.org/10.1109/SSCI47803.2020.9308510
LibreCat | DOI
 
[101]
2020 | Conference Paper | LibreCat-ID: 46320
Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020). A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In G. Meiselwitz (Ed.), Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (pp. 201–214). Springer International Publishing. https://doi.org/10.1007/978-3-030-49570-1_14
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[100]
2020 | Conference Paper | LibreCat-ID: 46325
Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). Towards Automated Configuration of Stream Clustering Algorithms. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19), 137–143. https://doi.org/10.1007/978-3-030-43823-4_12
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[99]
2020 | Conference Paper | LibreCat-ID: 46321
Assenmacher, D., Frischlich , L., Trautmann, H., Grimme, C., & Adam, L. (2020). Inside the tool set of automation: Free social bot code revisited. In C. Grimme, M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in open online media (pp. 101–114). Springer.
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[98]
2020 | Conference Paper | LibreCat-ID: 46326
Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020), 80–95. https://doi.org/10.1007/978-3-030-53552-0_10
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[97]
2020 | Conference Paper | LibreCat-ID: 46324
Bossek, J., Kerschke, P., & Trautmann, H. (2020). Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8.
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[96]
2020 | Conference Paper | LibreCat-ID: 46322
Bossek, J., Grimme, C., Rudolph, G., & Trautmann, H. (2020). Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8. https://doi.org/10.1109/CEC48606.2020.9185778
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[95]
2020 | Conference Paper | LibreCat-ID: 46323
Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 166–174.
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[94]
2020 | Conference Paper | LibreCat-ID: 46327
Lena, C., Frischlich, L., Trautmann, H., & Grimme, C. (2020). Automated detection of nostalgic text in the context of societal pessimism. In C. Grimme, M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in open online media (pp. 48–58).
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[93]
2020 | Conference Paper | LibreCat-ID: 46330
Seiler, M. V., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, & H. Trautmann (Eds.), Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI) (pp. 48–64). https://doi.org/10.1007/978-3-030-58112-1_4
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[92]
2020 | Conference Paper | LibreCat-ID: 46329
Riehle, D. M., Niemann, M., Brunk, J., Assenmacher, D., Trautmann, H., & Becker, J. (2020). Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation Tool. In G. Meiselwitz (Ed.), Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing (pp. 71–86). Springer International Publishing.
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[91]
2020 | Journal Article | LibreCat-ID: 46333
Assenmacher, D., Clever, L., Frischlich, L., Quandt, T., Trautmann, H., & Grimme, C. (2020). Demystifying Social Bots: On the Intelligence of Automated Social Media Actors. Social Media + Society, 6(3), 2056305120939264. https://doi.org/10.1177/2056305120939264
LibreCat | DOI
 
[90]
2020 | Journal Article | LibreCat-ID: 46334
Bossek, J., Kerschke, P., & Trautmann, H. (2020). A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Applied Soft Computing, 88, 105901. https://doi.org/10.1016/j.asoc.2019.105901
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[89]
2020 | Conference Paper | LibreCat-ID: 46331
Seiler, M. V., Trautmann, H., & Kerschke, P. (2020). Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries. Proceedings of the International Joint Conference on Neural Networks (IJCNN), 1–8. https://doi.org/10.1109/IJCNN48605.2020.9207338
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[88]
2020 | Conference Paper | LibreCat-ID: 46332
Steinhoff, V., Kerschke, P., Aspar, P., Trautmann, H., & Grimme, C. (2020). Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 2445–2452. https://doi.org/10.1109/SSCI47803.2020.9308259
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[87]
2019 | Conference Paper | LibreCat-ID: 46338
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 516–528). Springer International Publishing. https://doi.org/10.1007/978-3-030-12598-1_41
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[86]
2019 | Conference Paper | LibreCat-ID: 46343
Grimme, C., Kerschke, P., & Trautmann, H. (2019). Multimodality in Multi-Objective Optimization — More Boon than Bane? In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 126–138). Springer. https://doi.org/10.1007/978-3-030-12598-1_11
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[85]
2019 | Journal Article | LibreCat-ID: 46345
Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated Algorithm Selection: Survey and Perspectives. Evolutionary Computation (ECJ), 27(1), 3–45. https://doi.org/10.1162/evco_a_00242
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[84]
2019 | Conference Paper | LibreCat-ID: 46339
Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. In T. Friedrich, C. Doerr, & D. Arnold (Eds.), Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV) (pp. 58–71). https://doi.org/10.1145/3299904.3340307
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[83]
2019 | Conference Paper | LibreCat-ID: 46337
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. Pardalos (Eds.), Learning and Intelligent Optimization (Vol. 11353, pp. 215–219). Springer.
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[82]
2019 | Journal Article | LibreCat-ID: 46344
Carnein, M., & Trautmann, H. (2019). Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms. Business and Information Systems Engineering (BISE), 61(3), 277–297.
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[81]
2019 | Conference Paper | LibreCat-ID: 46340
Carnein, M., Homann, L., Trautmann, H., & Vossen, G. (2019). A Recommender System Based on Omni-Channel Customer Data. Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 65–74.
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[80]
2019 | Conference Paper | LibreCat-ID: 46341
Carnein, M., & Trautmann, H. (2019). Customer Segmentation Based on Transactional Data Using Stream Clustering. Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), 280–292.
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[79]
2019 | Conference Paper | LibreCat-ID: 46342
Grimme, C., Kerschke, P., Emmerich, M. T. M., Preuss, M., Deutz, A. H., & Trautmann, H. (2019). Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization. AIP Conference Proceedings, 020052-1-020052–020054. https://doi.org/10.1063/1.5090019
LibreCat | DOI
 
[78]
2019 | Book Chapter | LibreCat-ID: 46336
Kerschke, P., & Trautmann, H. (2019). Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-package flacco. In N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, & M. Vichi (Eds.), Applications in Statistical Computing (pp. 93–123). Springer. https://doi.org/10.1007/978-3-030-25147-5_7
LibreCat | DOI
 
[77]
2019 | Book | LibreCat-ID: 46335
Trautmann, H. (2019). Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement. Springer International Publishing.
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[76]
2019 | Journal Article | LibreCat-ID: 46346
Kerschke, P., & Trautmann, H. (2019). Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning. Evolutionary Computation (ECJ), 27(1), 99–127. https://doi.org/10.1162/evco_a_00236
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[75]
2019 | Journal Article | LibreCat-ID: 46347
Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2019). Search Dynamics on Multimodal Multi-Objective Problems. Evolutionary Computation (ECJ), 27(4), 577–609. https://doi.org/10.1162/evco_a_00234
LibreCat | DOI
 
[74]
2018 | Conference Paper | LibreCat-ID: 46350
van Engelen, J. E., van Lier, J. J., Takes, F. W., & Trautmann, H. (2018). Accurate WiFi based indoor positioning with continuous location sampling. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), 524–540.
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[73]
2018 | Conference Paper | LibreCat-ID: 46348
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
LibreCat | DOI
 
[72]
2018 | Journal Article | LibreCat-ID: 46351
Carnein, M., & Trautmann, H. (2018). evoStream — Evolutionary Stream Clustering Utilizing Idle Times. Big Data Research, 14, 101–111. https://doi.org/10.1016/j.bdr.2018.05.005
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[71]
2018 | Journal Article | LibreCat-ID: 46353
Li, L., Wang, Y., Trautmann, H., Jing, N., & Emmerich, M. (2018). Multiobjective evolutionary algorithms based on target region preferences. Swarm and Evolutionary Computation, 40, 196–215. https://doi.org/10.1016/j.swevo.2018.02.006
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[70]
2018 | Journal Article | LibreCat-ID: 46352
Kerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H., & Trautmann, H. (2018). Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation (ECJ), 26(4), 597–620. https://doi.org/10.1162/evco_a_00215
LibreCat | DOI
 
[69]
2018 | Conference Paper | LibreCat-ID: 46349
Kerschke, P., Bossek, J., & Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’18) Companion, 1737–1744. https://doi.org/10.1145/3205651.3208233
LibreCat | DOI
 
[68]
2017 | Book Chapter | LibreCat-ID: 46355
Adrián, S. H. V., Lara, A., Trautmann, H., Rudolph, G., & Schütze, O. (2017). The Directed Search Method for Unconstrained Parameter Dependent Multi-objective Optimization Problems. In O. Schütze, L. Trujillo, P. Legrand, & Y. Maldonado (Eds.), NEO 15 (pp. 281–330). Springer International Publishing. https://doi.org/10.1007/978-3-319-44003-3_12
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[67]
2017 | Conference Paper | LibreCat-ID: 46360
Carnein, M., Heuchert, M., Homann, L., Trautmann, H., Vossen, G., Becker, J., & Kraume, K. (2017). Towards Efficient and Informative Omni-Channel Customer Relationship Management. In S. de Cesare & F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17) (Vol. 10651, pp. 69–78). Springer International Publishing. https://doi.org/10.1007/978-3-319-70625-2_7
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[66]
2017 | Conference Paper | LibreCat-ID: 46361
Carnein, M., Homann, L., Trautmann, H., Vossen, G., & Kraume, K. (2017). Customer Service in Social Media — An Empirical Study of the Airline Industry. In N. Ritter, H. Schwarz, M. Klettke, A. Thor, O. Kopp, & M. W. Bernhard (Eds.), Proceedings of the 17$^th$ Conference on Database Systems for Business, Technology, and Web (BTW ’17): Vol. P-266 (pp. 33–40). Gesellschaft für Informatik.
LibreCat
 
[65]
2017 | Book Chapter | LibreCat-ID: 46356
Li, L., Yevseyeva, I., Basto-Fernandes, V., Trautmann, H., Jing, N., & Emmerich, M. (2017). Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, & C. Grimme (Eds.), Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 406–421). Springer International Publishing. https://doi.org/10.1007/978-3-319-54157-0_28
LibreCat | DOI
 
[64]
2017 | Book Chapter | LibreCat-ID: 46357
Tierney, K., Handali, J., Grimme, C., & Trautmann, H. (2017). Multi-objective Optimization for Liner Shipping Fleet Repositioning. In H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, & C. Grimme (Eds.), Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 622–638). Springer International Publishing. https://doi.org/10.1007/978-3-319-54157-0_42
LibreCat | DOI
 
[63]
2017 | Conference Paper | LibreCat-ID: 46359
Carnein, M., Assenmacher, D., & Trautmann, H. (2017). Stream Clustering of Chat Messages with Applications to Twitch Streams. In S. de Cesare & F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17) (pp. 79–88). Springer International Publishing. https://doi.org/10.1007/978-3-319-70625-2_8
LibreCat | DOI
 
[62]
2017 | Journal Article | LibreCat-ID: 46362
Grimme, C., Preuss, M., Adam, L., & Trautmann, H. (2017). Social Bots: Human-Like by Means of Human Control? Big Data, 5(4), 279–293. https://doi.org/10.1089/big.2017.0044
LibreCat | DOI
 
[61]
2017 | Conference Paper | LibreCat-ID: 46358
Carnein, M., Assenmacher, D., & Trautmann, H. (2017). An Empirical Comparison of Stream Clustering Algorithms. Proceedings of the ACM International Conference on Computing Frontiers (CF ’17), 361–365. https://doi.org/10.1145/3075564.3078887
LibreCat | DOI
 
[60]
2016 | Conference Paper | LibreCat-ID: 46364
Blot, A., Hoos, H., Jourdan, L., Marmion, M., & Trautmann, H. (2016). MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In V. et al. Joaquin (Ed.), LION 2016: Learning and Intelligent Optimization (Vol. 10079, pp. 32–47). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_3
LibreCat | DOI
 
[59]
2016 | Book Chapter | LibreCat-ID: 46363
Rudolph, G., Schütze, O., & Trautmann, H. (2016). On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. In G. Squillero & P. Burelli (Eds.), Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II (pp. 42–55). Springer International Publishing. https://doi.org/10.1007/978-3-319-31153-1_4
LibreCat | DOI
 
[58]
2016 | Conference Paper | LibreCat-ID: 46365
Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization (Vol. 10079, pp. 48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
LibreCat | DOI
 
[57]
2016 | Conference Paper | LibreCat-ID: 46366
Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In G. Adorni, S. Cagnoni, M. Gori, & M. Maratea (Eds.), AI*IA 2016 Advances in Artificial Intelligence (Vol. 10037, pp. 3–12). Springer. https://doi.org/10.1007/978-3-319-49130-1_1
LibreCat | DOI
 
[56]
2016 | Conference Paper | LibreCat-ID: 46369
Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2016). Towards Analyzing Multimodality of Multiobjective Landscapes. Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV), 962–972. https://doi.org/10.1007/978-3-319-45823-6_90
LibreCat | DOI
 
[55]
2016 | Conference Paper | LibreCat-ID: 46367
Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236. https://doi.org/10.1145/2908812.2908845
LibreCat | DOI
 
[54]
2016 | Journal Article | LibreCat-ID: 46371
Rudolph, G., Schütze, O., Grimme, C., Domínguez-Medina, C., & Trautmann, H. (2016). Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results. Computational Optimization and Applications (Comput. Optim. Appl.), 64(2), 589–618. https://doi.org/10.1007/s10589-015-9815-8
LibreCat | DOI
 
[53]
2016 | Journal Article | LibreCat-ID: 46372
Schütze, O., Sosa, H. V., Trautmann, H., & Rudolph, G. (2016). The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. Journal of Heuristics, 22(3), 273–300. https://doi.org/10.1007/s10732-016-9310-0
LibreCat | DOI
 
[52]
2016 | Conference Paper | LibreCat-ID: 46368
Kerschke, P., & Trautmann, H. (2016). The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems. Proceedings of the IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2016.7748359
LibreCat | DOI
 
[51]
2016 | Journal Article | LibreCat-ID: 46370
Neumann, F., & Trautmann, H. (2016). Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). Dagstuhl Reports, 5(5), 78–79. https://doi.org/10.4230/DagRep.5.5.57
LibreCat | DOI
 
[50]
2015 | Conference Paper | LibreCat-ID: 46373
Chinnov, A., Kerschke, P., Meske, C., Stieglitz, S., & Trautmann, H. (2015). An Overview of Topic Discovery in Twitter Communication through Social Media Analytics. Proceedings of the 20$^th$ Americas Conference on Information Systems (AMCIS ’15), 1–10.
LibreCat
 
[49]
2015 | Conference Paper | LibreCat-ID: 46375
Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2015). Detecting Funnel Structures by Means of Exploratory Landscape Analysis. In S. Silva (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15) (pp. 265–272). ACM. https://doi.org/10.1145/2739480.2754642
LibreCat | DOI
 
[48]
2015 | Conference Paper | LibreCat-ID: 46377
Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15), 425–432. https://doi.org/10.1145/2739480.2754705
LibreCat | DOI
 
[47]
2015 | Conference Paper | LibreCat-ID: 46376
Kotthoff, L., Kerschke, P., Hoos, H., & Trautmann, H. (2015). Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection. In C. Dhaenens, L. Jourdan, & M.-E. Marmion (Eds.), Learning and Intelligent Optimization (pp. 202–217). Springer International Publishing.
LibreCat
 
[46]
2015 | Journal Article | LibreCat-ID: 46379
Brockhoff, D., Wagner, T., & Trautmann, H. (2015). R2 Indicator Based Multiobjective Search. Evolutionary Computation Journal, 23(3), 369–395. https://doi.org/10.1162/EVCO_a_00135
LibreCat | DOI
 
[45]
2015 | Conference Paper | LibreCat-ID: 46374
Grimme, C., Meisel, S., Trautmann, H., Rudolph, G., & Wölck, M. (2015). Multi-Objective Analysis of Approaches to Dynamic Routing Of a Vehicle. Proceedings of the European Conference On Information Systems.
LibreCat
 
[44]
2015 | Journal Article | LibreCat-ID: 46380
Mersmann, O., Preuss, M., Trautmann, H., Bischl, B., & Weihs, C. (2015). Analyzing the BBOB Results by Means of Benchmarking Concepts. Evolutionary Computation Journal, 23(1), 161–185.
LibreCat
 
[43]
2014 | Book Chapter | LibreCat-ID: 46381
Kerschke, P., Preuss, M., Hernández, C., Schütze, O., Sun, J.-Q., Grimme, C., Rudolph, G., Bischl, B., & Trautmann, H. (2014). Cell Mapping Techniques for Exploratory Landscape Analysis. In A.-A. Tantar, E. Tantar, J.-Q. Sun, W. Zhang, Q. Ding, O. Schütze, M. T. M. Emmerich, P. Legrand, M. P. Del, & C. C. A. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 115–131). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_9
LibreCat | DOI
 
[42]
2014 | Book Chapter | LibreCat-ID: 46382
Rudolph, G., Schütze, O., Grimme, C., & Trautmann, H. (2014). A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets. In A. Tantar, E. Tantar, J. Sun, W. Zhang, Q. Ding, O. Schütze, M. Emmerich, P. Legrand, M. P. Del, & C. C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 261–273). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_18
LibreCat | DOI
 
[41]
2014 | Conference Paper | LibreCat-ID: 46383
Rudolph, G., Grimme, C., Schütze, O., & Trautmann, H. (2014). An Aspiration Set EMOA Based on Averaged Hausdorff Distances. Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), 8426, 153–156.
LibreCat
 
[40]
2014 | Conference Paper | LibreCat-ID: 46384
Wessing, S., Preuss, M., & Trautmann, H. (2014). Stopping Criteria for Multimodal Optimization. In T. Bartz-Beielstein, J. Branke, B. Filipic, & J. Smith (Eds.), Proceedings of the Parallel Problem Solving from Nature — PPSN XIII (Vol. 8672, pp. 141–150). Springer. https://doi.org/10.1007/978-3-319-10762-2_14
LibreCat | DOI
 
[39]
2013 | Book Chapter | LibreCat-ID: 46385
Sosa, H. V., Schütze, O., Rudolph, G., & Trautmann, H. (2013). The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. In M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, & C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV (Vol. 227, pp. 189–205). Springer International Publishing. https://doi.org/10.1007/978-3-319-01128-8_13
LibreCat | DOI
 
[38]
2013 | Book Chapter | LibreCat-ID: 46386
Trautmann, H., Rudolph, G., Dominguez-Medina, C., & Schütze, O. (2013). Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems. In O. Schütze, C. C. Coello, A. Tantar, E. Tantar, P. Bouvry, M. P. Del, & P. Legrand (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (Vol. 175, pp. 89–105). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_6
LibreCat | DOI
 
[37]
2013 | Conference Paper | LibreCat-ID: 46388
Nallaperuma, S., Wagner, M., Neumann, F., Bischl, B., Mersmann, O., & Trautmann, H. (2013). A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem. Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII, 147–160. https://doi.org/10.1145/2460239.2460253
LibreCat | DOI
 
[36]
2013 | Conference Paper | LibreCat-ID: 46390
Rudolph, G., Trautmann, H., Sengupta, S., & Schütze, O. (2013). Evenly Spaced Pareto Front Approximations for Tricriteria Problems Based on Triangulation. In R. Purshouse, P. Fleming, C. Fonseca, S. Greco, & J. Shaw (Eds.), Evolutionary Multi-Criterion Optimization — 7$^th$ International Conference, EMO 2013, Sheffield, UK, Proceedings (Vol. 7811, pp. 443–458). Springer. https://doi.org/10.1007/978-3-642-37140-0_34
LibreCat | DOI
 
[35]
2013 | Conference Paper | LibreCat-ID: 46391
Sosa-Hernandez, V., Schütze, O., Rudoph, G., & Trautmann, H. (2013). Directed Search Method for Indicator-based Multi-objective Evolutionary Algorithms. Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion, 1699–1702. https://doi.org/10.1145/2464576.2482756
LibreCat | DOI
 
[34]
2013 | Conference Paper | LibreCat-ID: 46387
Dominguez-Medina, C., Rudolph, G., Schütze, O., & Trautmann, H. (2013). Evenly spaced Pareto fronts of quad-objective problems using PSA partitioning technique. Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC), 3190–3197. https://doi.org/10.1109/CEC.2013.6557960
LibreCat | DOI
 
[33]
2013 | Conference Paper | LibreCat-ID: 46389
Preuss, M., Kozakowski, D., Hagelbäck, J., & Trautmann, H. (2013). Reactive strategy choice in StarCraft by means of Fuzzy Control. 2013 IEEE Conference on Computational Inteligence in Games (CIG), 1–8. https://doi.org/10.1109/CIG.2013.6633627
LibreCat | DOI
 
[32]
2013 | Journal Article | LibreCat-ID: 46395
Trautmann, H., Wagner, T., Biermann, D., & Weihs, C. (2013). Indicator-based Selection in Evolutionary Multiobjective Optimization Algorithms Based On the Desirability Index. Journal of Multi-Criteria Decision Analysis, 20(5–6), 319–337. https://doi.org/10.1002/mcda.1503
LibreCat | DOI
 
[31]
2013 | Conference Paper | LibreCat-ID: 46393
Wagner, T., Trautmann, H., & Brockhoff, D. (2013). Preference Articulation by Means of the R2 Indicator. In R. C. Purshouse, P. J. Fleming, C. M. Fonseca, S. Greco, & J. Shaw (Eds.), Evolutionary Multi-Criterion Optimization (pp. 81–95). Springer Berlin Heidelberg.
LibreCat
 
[30]
2013 | Conference Paper | LibreCat-ID: 46392
Trautmann, H., Wagner, T., & Brockhoff, D. (2013). R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. In G. Nicosia & P. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 70–74). Springer Berlin Heidelberg.
LibreCat
 
[29]
2013 | Journal Article | LibreCat-ID: 46394
Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. Annals of Mathematics and Artificial Intelligence, 69, 151–182.
LibreCat
 
[28]
2012 | Conference Paper | LibreCat-ID: 46397
Brockhoff, D., Wagner, T., & Trautmann, H. (2012). On the Properties of the R2 Indicator. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, 465–472. https://doi.org/10.1145/2330163.2330230
LibreCat | DOI
 
[27]
2012 | Conference Paper | LibreCat-ID: 46396
Bischl, B., Mersmann, O., Trautmann, H., & Preuß, M. (2012). Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, 313–320. https://doi.org/10.1145/2330163.2330209
LibreCat | DOI
 
[26]
2012 | Conference Paper | LibreCat-ID: 46398
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. In Y. Hamadi & M. Schoenauer (Eds.), Learning and Intelligent Optimization (pp. 115–129). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_9
LibreCat | DOI
 
[25]
2012 | Journal Article | LibreCat-ID: 46399
Bischl, B., Mersmann, O., Trautmann, H., & Weihs, C. (2012). Resampling Methods in Model Validation. Evolutionary Computation Journal, 20(2), 249–275. https://doi.org/10.1162/EVCO_a_00069
LibreCat | DOI
 
[24]
2012 | Journal Article | LibreCat-ID: 46400
Rudolph, G., Trautmann, H., & Schütze, O. (2012). Homogene Approximation der Paretofront bei mehrkriteriellen Kontrollproblemen. At-Automatisierungstechnik, 60, 610–621. https://doi.org/10.1524/auto.2012.1033
LibreCat | DOI
 
[23]
2011 | Conference Paper | LibreCat-ID: 46401
Mersmann, O., Bischl, B., Trautmann, H., Preuss, M., Weihs, C., & Rudolph, G. (2011). Exploratory Landscape Analysis. Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, 829–836. https://doi.org/10.1145/2001576.2001690
LibreCat | DOI
 
[22]
2011 | Conference Paper | LibreCat-ID: 46402
Wagner, T., Trautmann, H., & Martí, L. (2011). A Taxonomy of Online Stopping Criteria for Multi-Objective Evolutionary Algorithms. In R. H. C. Takahashi, K. Deb, E. F. Wanner, & S. Greco (Eds.), Evolutionary Multi-Criterion Optimization (pp. 16–30). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_2
LibreCat | DOI
 
[21]
2011 | Journal Article | LibreCat-ID: 46403
Naujoks, B., Trautmann, H., Wessing, S., & Weihs, C. (2011). Advanced concepts for multi-objective evolutionary optimization in aircraft industry. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 225(10), 1081–1096. https://doi.org/10.1177/0954410011414120
LibreCat | DOI
 
[20]
2010 | Conference Paper | LibreCat-ID: 46408
Mostaghim, S., Trautmann, H., & Mersmann, O. (2010). Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 101–110). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_11
LibreCat | DOI
 
[19]
2010 | Conference Paper | LibreCat-ID: 46405
Mersmann, O., Preuss, M., & Trautmann, H. (2010). Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I, 73–82.
LibreCat
 
[18]
2010 | Conference Paper | LibreCat-ID: 46406
Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). On the Distribution of EMOA Hypervolumes. In C. Blum & R. Battiti (Eds.), Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy (Vol. 6073, pp. 333–337). Springer.
LibreCat
 
[17]
2010 | Conference Paper | LibreCat-ID: 46407
Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). Benchmarking evolutionary multiobjective optimization algorithms. IEEE Congress on Evolutionary Computation, 1–8. https://doi.org/10.1109/CEC.2010.5586241
LibreCat | DOI
 
[16]
2010 | Conference Paper | LibreCat-ID: 46404
Ding, J., Wessing, S., Trautmann, H., Mehnen, J., & Naujoks, B. (2010). Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing. In R. Teti (Ed.), Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10). Copyright C.O.C. Com. org. Conv.
LibreCat
 
[15]
2010 | Conference Paper | LibreCat-ID: 46409
Voß, T., Trautmann, H., & Igel, C. (2010). New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 260–269). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_27
LibreCat | DOI
 
[14]
2010 | Journal Article | LibreCat-ID: 46412
Wagner, T., & Trautmann, H. (2010). Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions. IEEE Transactions on Evolutionary Computation, 14(5), 688–701. https://doi.org/10.1109/TEVC.2010.2058119
LibreCat | DOI
 
[13]
2010 | Journal Article | LibreCat-ID: 46411
Azene, Y. T., Roy, R., Farrugia, D., Onisa, C., Mehnen, J., & Trautmann, H. (2010). Work roll cooling system design optimisation in presence of uncertainty and constrains. CIRP Journal of Manufacturing Science and Technology, 2(4), 290–298. https://doi.org/10.1016/j.cirpj.2010.06.001
LibreCat | DOI
 
[12]
2010 | Conference Paper | LibreCat-ID: 46410
Wagner, T., & Trautmann, H. (2010). Online convergence detection for evolutionary multi-objective algorithms revisited. IEEE Congress on Evolutionary Computation, 1–8. https://doi.org/10.1109/CEC.2010.5586474
LibreCat | DOI
 
[11]
2009 | Conference Paper | LibreCat-ID: 46414
Wagner, T., Trautmann, H., & Naujoks, B. (2009). OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing. In M. Ehrgott, C. M. Fonseca, X. Gandibleux, J.-K. Hao, & M. Sevaux (Eds.), Evolutionary Multi-Criterion Optimization (pp. 198–215). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-01020-0_19
LibreCat | DOI
 
[10]
2009 | Conference Paper | LibreCat-ID: 46415
Trautmann, H., Mehnen, J., & Naujoks, B. (2009). Pareto-dominance in noisy environments. 2009 IEEE Congress on Evolutionary Computation, 3119–3126. https://doi.org/10.1109/CEC.2009.4983338
LibreCat | DOI
 
[9]
2009 | Conference Paper | LibreCat-ID: 46413
Naujoks, B., & Trautmann, H. (2009). Online convergence detection for multiobjective aerodynamic applications. 2009 IEEE Congress on Evolutionary Computation, 332–339. https://doi.org/10.1109/CEC.2009.4982966
LibreCat | DOI
 
[8]
2009 | Journal Article | LibreCat-ID: 46416
Trautmann, H., & Mehnen, J. (2009). Statistical Methods for Improving Multi-objective Evolutionary Optimisation. International Journal of Computational Intelligence Research, 5(2), 72–78.
LibreCat
 
[7]
2009 | Journal Article | LibreCat-ID: 46418
Trautmann, H., Wagner, T., Naujoks, B., Preuss, M., & Mehnen, J. (2009). Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms. Evolutionary Computation, 17(4), 493–509. https://doi.org/10.1162/evco.2009.17.4.17403
LibreCat | DOI
 
[6]
2009 | Journal Article | LibreCat-ID: 46417
Trautmann, H., & Mehnen, J. (2009). Preference-based Pareto optimization in certain and noisy environments. Engineering Optimization, 41(1), 23–38. https://doi.org/10.1080/03052150802347926
LibreCat | DOI
 
[5]
2008 | Conference Paper | LibreCat-ID: 46420
Trautmann, H., Ligges, U., Mehnen, J., & Preuss, M. (2008). A Convergence Criterion for Multiobjective Evolutionary Algorithms Based on Systematic Statistical Testing. In G. Rudolph, T. Jansen, N. Beume, S. Lucas, & C. Poloni (Eds.), Parallel Problem Solving from Nature – PPSN X (pp. 825–836). Springer Berlin Heidelberg.
LibreCat
 
[4]
2008 | Conference Paper | LibreCat-ID: 46419
Mehnen, J., & Trautmann, H. (2008). Robust Multi-objective Optimisation of Weld Bead Geometry for Additive Manufacturing. In R. Teti (Ed.), Proceedings of the 6$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’08). Copyright C.O.C. Com. org. Conv.
LibreCat
 
[3]
2007 | Conference Paper | LibreCat-ID: 46421
Mehnen, J., Trautmann, H., & Tiwari, A. (2007). Introducing user preference using Desirability Functions in Multi-Objective Evolutionary Optimisation of noisy processes. 2007 IEEE Congress on Evolutionary Computation, 2687–2694. https://doi.org/10.1109/CEC.2007.4424810
LibreCat | DOI
 
[2]
2006 | Journal Article | LibreCat-ID: 46423
Trautmann, H., & Weihs, C. (2006). On the Distribution of the Desirability Index using Harrington’s Desirability Function. Metrika, 63(2), 207–213. https://doi.org/10.1007/s00184-005-0012-0
LibreCat | DOI
 
[1]
2006 | Conference Paper | LibreCat-ID: 46422
Mehnen, J., & Trautmann, H. (2006). Integration of Expert’s Preferences in Pareto Optimization by Desirability Function Techniques. In R. Teti (Ed.), CIRP ICME ’06) — Proceedings of the 5$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (pp. 293–298). C.O.C. Com. org. Conv. CIRP ICME ’06.
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