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143 Publications


2020 | Conference Paper | LibreCat-ID: 46319
D. Assenmacher, L. Adam, H. Trautmann, and C. Grimme, “Towards Real-Time and Unsupervised Campaign Detection in Social Media,” 2020.
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2020 | Conference Paper | LibreCat-ID: 46328
R. P. Prager, H. Trautmann, H. Wang, T. H. W. Bäck, and P. Kerschke, “Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 996–1003, doi: 10.1109/SSCI47803.2020.9308510.
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2020 | Conference Paper | LibreCat-ID: 46320
D. Assenmacher, L. Clever, J. Pohl, H. Trautmann, and C. Grimme, “A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media,” in Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis, 2020, pp. 201–214, doi: 10.1007/978-3-030-49570-1_14.
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2020 | Conference Paper | LibreCat-ID: 46325
M. Carnein, H. Trautmann, A. Bifet, and B. Pfahringer, “Towards Automated Configuration of Stream Clustering Algorithms,” in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19), 2020, pp. 137–143, doi: 10.1007/978-3-030-43823-4_12.
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2020 | Conference Paper | LibreCat-ID: 46321
D. Assenmacher, L. Frischlich , H. Trautmann, C. Grimme, and L. Adam, “Inside the tool set of automation: Free social bot code revisited,” in Disinformation in open online media, 2020, pp. 101–114.
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2020 | Conference Paper | LibreCat-ID: 46326
M. Carnein, H. Trautmann, A. Bifet, and B. Pfahringer, “confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms,” in Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020), 2020, pp. 80–95, doi: 10.1007/978-3-030-53552-0_10.
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2020 | Conference Paper | LibreCat-ID: 46327
C. Lena, L. Frischlich, H. Trautmann, and C. Grimme, “Automated detection of nostalgic text in the context of societal pessimism,” in Disinformation in open online media, 2020, pp. 48–58.
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2020 | Conference Paper | LibreCat-ID: 46329
D. M. Riehle, M. Niemann, J. Brunk, D. Assenmacher, H. Trautmann, and J. Becker, “Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation Tool,” in Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing, 2020, pp. 71–86.
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2020 | Journal Article | LibreCat-ID: 46333
D. Assenmacher, L. Clever, L. Frischlich, T. Quandt, H. Trautmann, and C. Grimme, “Demystifying Social Bots: On the Intelligence of Automated Social Media Actors,” Social Media + Society, vol. 6, no. 3, p. 2056305120939264, 2020, doi: 10.1177/2056305120939264.
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2020 | Conference Paper | LibreCat-ID: 46332
V. Steinhoff, P. Kerschke, P. Aspar, H. Trautmann, and C. Grimme, “Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 2445–2452, doi: 10.1109/SSCI47803.2020.9308259.
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2020 | Conference Paper | LibreCat-ID: 46331
M. Seiler, H. Trautmann, and P. Kerschke, “Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2020, pp. 1–8, doi: 10.1109/IJCNN48605.2020.9207338.
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2020 | Conference Paper | LibreCat-ID: 46330
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem,” in Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI), 2020, pp. 48–64, doi: 10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 46334
J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms,” Applied Soft Computing, vol. 88, p. 105901, 2020, doi: https://doi.org/10.1016/j.asoc.2019.105901.
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2020 | Conference Paper | LibreCat-ID: 46322
J. Bossek, C. Grimme, G. Rudolph, and H. Trautmann, “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8, doi: 10.1109/CEC48606.2020.9185778.
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2020 | Conference Paper | LibreCat-ID: 46324
J. Bossek, P. Kerschke, and H. Trautmann, “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 46323
J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 2020, pp. 166–174.
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2019 | Conference Paper | LibreCat-ID: 46343
C. Grimme, P. Kerschke, and H. Trautmann, “Multimodality in Multi-Objective Optimization — More Boon than Bane?,” in Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), 2019, vol. 11411, pp. 126–138, doi: 10.1007/978-3-030-12598-1_11.
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2019 | Journal Article | LibreCat-ID: 46345
P. Kerschke, H. H. Hoos, F. Neumann, and H. Trautmann, “Automated Algorithm Selection: Survey and Perspectives,” Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 3–45, 2019, doi: 10.1162/evco_a_00242.
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2019 | Journal Article | LibreCat-ID: 46344
M. Carnein and H. Trautmann, “Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms,” Business and Information Systems Engineering (BISE), vol. 61, no. 3, pp. 277–297, 2019.
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2019 | Conference Paper | LibreCat-ID: 46340
M. Carnein, L. Homann, H. Trautmann, and G. Vossen, “A Recommender System Based on Omni-Channel Customer Data,” in Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 2019, pp. 65–74.
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