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143 Publications
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.
LibreCat
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
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| DOI
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
LibreCat
| DOI
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
LibreCat
| DOI
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.
LibreCat
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
LibreCat
| DOI
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).
LibreCat
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.
LibreCat
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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| DOI
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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| DOI
2020 | Conference Paper | LibreCat-ID: 46331
Seiler, M., 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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| DOI
2020 | Conference Paper | LibreCat-ID: 46330
Seiler, M., 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
LibreCat
| DOI
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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| DOI
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
LibreCat
| DOI
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.
LibreCat
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.
LibreCat
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
LibreCat
| DOI
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
LibreCat
| DOI
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.
LibreCat
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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