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191 Publications


2024 | Conference Paper | LibreCat-ID: 52749
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP
M. Vinzent Seiler, J. Rook, J. Heins, O.L. Preuß, J. Bossek, H. Trautmann, in: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2024.
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2024 | Book Chapter | LibreCat-ID: 52759
On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems
O.L. Preuß, J. Rook, H. Trautmann, in: Applications of Evolutionary Computation, Springer Nature Switzerland, Cham, 2024.
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2023 | Journal Article | LibreCat-ID: 46299
Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python
R.P. Prager, H. Trautmann, Evolutionary Computation (2023) 1–25.
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2023 | Journal Article | LibreCat-ID: 48871
Do Additional Target Points Speed Up Evolutionary Algorithms?
J. Bossek, D. Sudholt, Theoretical Computer Science (2023) 113757.
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2023 | Journal Article | LibreCat-ID: 48859 LibreCat | DOI
 

2023 | Journal Article | LibreCat-ID: 46310
A study on the effects of normalized TSP features for automated algorithm selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, Theoretical Computer Science 940 (2023) 123–145.
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2023 | Conference Paper | LibreCat-ID: 47522
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features
R.P. Prager, K. Dietrich, L. Schneider, L. Schäpermeier, B. Bischl, P. Kerschke, H. Trautmann, O. Mersmann, in: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2023, pp. 129–139.
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2023 | Conference Paper | LibreCat-ID: 46297
Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features
R.P. Prager, H. Trautmann, in: J. Correia, S. Smith, R. Qaddoura (Eds.), Applications of Evolutionary Computation, Springer Nature Switzerland, Cham, 2023, pp. 411–425.
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2023 | Conference Paper | LibreCat-ID: 46298
Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets
L. Schäpermeier, P. Kerschke, C. Grimme, H. Trautmann, in: M. Emmerich, A. Deutz, H. Wang, A.V. Kononova, B. Naujoks, K. Li, K. Miettinen, I. Yevseyeva (Eds.), Evolutionary Multi-Criterion Optimization, Springer Nature Switzerland, Cham, 2023, pp. 291–304.
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2023 | Conference Paper | LibreCat-ID: 48869
On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem
J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 248–256.
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2023 | Conference Paper | LibreCat-ID: 48872
Runtime Analysis of Quality Diversity Algorithms
J. Bossek, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 1546–1554.
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2023 | Conference Paper | LibreCat-ID: 48886
Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space
A. Marrero, E. Segredo, E. Hart, J. Bossek, A. Neumann, in: Proceedings of the Genetic} and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 312–320.
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2023 | Conference Paper | LibreCat-ID: 52530
Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems
R.P. Prager, H. Trautmann, 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, ACM, 2023, pp. 451–454.
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2023 | Conference Paper | LibreCat-ID: 48898
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP
M.V. Seiler, J. Rook, J. Heins, O.L. Preuß, J. Bossek, H. Trautmann, in: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), n.d., pp. 361–368.
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2022 | Journal Article | LibreCat-ID: 46316
Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem
D. Assenmacher, D. Weber, M. Preuss, A.C. Valdez, A. Bradshaw, B. Ross, S. Cresci, H. Trautmann, F. Neumann, C. Grimme, Social Science Computer Review 40 (2022) 1496–1522.
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2022 | Journal Article | LibreCat-ID: 46309
Process-Oriented Stream Classification Pipeline: A Literature Review
L. Clever, J.S. Pohl, J. Bossek, P. Kerschke, H. Trautmann, Applied Sciences 12 (2022) 1–44.
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2022 | Journal Article | LibreCat-ID: 46308
The objective that freed me: a multi-objective local search approach for continuous single-objective optimization
P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, C. Grimme, Natural Computing 1 (2022) 1–15.
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2022 | Journal Article | LibreCat-ID: 48878
Process-Oriented Stream Classification Pipeline: A Literature Review
L. Clever, J.S. Pohl, J. Bossek, P. Kerschke, H. Trautmann, Applied Sciences 12 (2022) 9094.
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2022 | Journal Article | LibreCat-ID: 52532
Estimation of component reliability from superposed renewal processes by means of latent variables
A.S. Rodrigues, P. Kerschke, C.A.D.B. Pereira, H. Trautmann, C. Wagner, B. Hellingrath, A. Polpo, Comput. Stat. 37 (2022) 355–379.
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2022 | Conference Paper | LibreCat-ID: 46301
Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption
D. Assenmacher, H. Trautmann, in: T. et al. Tran (Ed.), Intelligent Information and Database Systems, Springer International Publishing, Cham, 2022, pp. 3–16.
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2022 | Conference Paper | LibreCat-ID: 46306
HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis
L. Schneider, L. Schäpermeier, R.P. Prager, B. Bischl, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 575–589.
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2022 | Conference Paper | LibreCat-ID: 46307
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
M.V. Seiler, R.P. Prager, P. Kerschke, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2022, pp. 657–665.
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2022 | Conference Paper | LibreCat-ID: 46304
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods
R.P. Prager, M.V. Seiler, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.
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2022 | Conference Paper | LibreCat-ID: 46303
Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches
J.S. Pohl, D. Assenmacher, M.V. Seiler, H. Trautmann, C. Grimme, in: for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM), AAAI Press, Palo Alto, CA, USA, 2022, pp. 1–10.
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2022 | Conference Paper | LibreCat-ID: 46305
On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: J. Fieldsend, M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359–356–359.
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2022 | Conference Paper | LibreCat-ID: 46302
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 192–206.
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2022 | Conference Paper | LibreCat-ID: 48861
Exploring the Feature Space of TSP Instances Using Quality Diversity
J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2022, pp. 186–194.
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2022 | Conference Paper | LibreCat-ID: 48868
Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA
J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 824–842.
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2022 | Conference Paper | LibreCat-ID: 48882
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 192–206.
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2022 | Conference Paper | LibreCat-ID: 48894
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\v sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.
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2022 | Conference Paper | LibreCat-ID: 48896
On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.
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2022 | Book Chapter | LibreCat-ID: 46300
(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse
M. Niemann, D. Assenmacher, J. Brunk, D.M. Riehle, J. Becker, H. Trautmann, in: G. Weitzel, S. Mündges (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen, VS Verlag für Sozialwissenschaften, Wiesbaden, 2022, pp. 249–274.
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2021 | Journal Article | LibreCat-ID: 46318
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization
C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers & Operations Research 136 (2021) 105489.
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2021 | Journal Article | LibreCat-ID: 46317
What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective
C. Coombs, P. Stacey, P. Kawalek, B. Simeonova, J. Becker, K. Bergener, J.Á. Carvalho, M. Fantinato, N.F. Garmann-Johnsen, C. Grimme, A. Stein, H. Trautmann, International Journal of Information Management 58 (2021).
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2021 | Journal Article | LibreCat-ID: 48854
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem
J. Bossek, F. Neumann, P. Peng, D. Sudholt, Algorithmica 83 (2021) 3148–3179.
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2021 | Conference Paper | LibreCat-ID: 46313
On the Potential of Normalized TSP Features for Automated Algorithm Selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: for Computing Machinery Association (Ed.), Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA XVI), Association for Computing Machinery, Dornbirn, Austria, 2021, pp. 1–15.
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2021 | Conference Paper | LibreCat-ID: 46311
Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization
P. Aspar, P. Kerschke, V. Steinhoff, H. Trautmann, C. Grimme, in: H. et al. Ishibuchi (Ed.), Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings, Springer, Heidelberg, Berlin, 2021, pp. 311–322.
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2021 | Conference Paper | LibreCat-ID: 46315
Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization
R.P. Prager, M. Vinzent Seiler, H. Trautmann, P. Kerschke, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021, pp. 1–8.
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2021 | Conference Paper | LibreCat-ID: 46312
RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets
D. Assenmacher, M. Niemann, K. Müller, M.V. Seiler, D.M. Riehle, H. Trautmann, in: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), Virtual Event, 2021, pp. 1–14.
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2021 | Conference Paper | LibreCat-ID: 48853
Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms
J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 556–564.
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2021 | Conference Paper | LibreCat-ID: 48855
Exact Counting and~Sampling of Optima for the Knapsack Problem
J. Bossek, A. Neumann, F. Neumann, in: Learning and Intelligent Optimization, Springer-Verlag, Berlin, Heidelberg, 2021, pp. 40–54.
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2021 | Conference Paper | LibreCat-ID: 48860
Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem
J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 198–206.
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2021 | Conference Paper | LibreCat-ID: 48876
Generating Instances with Performance Differences for More than Just Two Algorithms
J. Bossek, M. Wagner, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1423–1432.
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2021 | Conference Paper | LibreCat-ID: 48893
Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem
A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 600–608.
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2021 | Conference Paper | LibreCat-ID: 48891
Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions
A. Neumann, J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 261–269.
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2021 | Book Chapter | LibreCat-ID: 48862
Do Additional Optima Speed up Evolutionary Algorithms?
J. Bossek, D. Sudholt, in: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.
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2021 | Book Chapter | LibreCat-ID: 48881
On the Potential of Normalized TSP Features for Automated Algorithm Selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–15.
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2021 | Book Chapter | LibreCat-ID: 48892
Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation
A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.
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2020 | Journal Article | LibreCat-ID: 46333
Demystifying Social Bots: On the Intelligence of Automated Social Media Actors
D. Assenmacher, L. Clever, L. Frischlich, T. Quandt, H. Trautmann, C. Grimme, Social Media + Society 6 (2020) 2056305120939264.
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2020 | Journal Article | LibreCat-ID: 46334 LibreCat | DOI
 

2020 | Journal Article | LibreCat-ID: 48848 LibreCat | DOI
 

2020 | Journal Article | LibreCat-ID: 48836
Benchmarking in Optimization: Best Practice and Open Issues
T. Bartz-Beielstein, C. Doerr, D. van den Berg, J. Bossek, S. Chandrasekaran, T. Eftimov, A. Fischbach, P. Kerschke, W.L. Cava, M. Lopez-Ibanez, K.M. Malan, J.H. Moore, B. Naujoks, P. Orzechowski, V. Volz, M. Wagner, T. Weise, Corr (2020).
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2020 | Conference Paper | LibreCat-ID: 46319
Towards Real-Time and Unsupervised Campaign Detection in Social Media
D. Assenmacher, L. Adam, H. Trautmann, C. Grimme, in: Proceedings of the Florida Artificial Intelligence Research Society Conference, Florida, USA, 2020.
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2020 | Conference Paper | LibreCat-ID: 46328
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis
R.P. Prager, H. Trautmann, H. Wang, T.H.W. Bäck, P. Kerschke, in: Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, 2020, pp. 996–1003.
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2020 | Conference Paper | LibreCat-ID: 46320
A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media
D. Assenmacher, L. Clever, J. Pohl, H. Trautmann, C. Grimme, 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, Springer International Publishing, Cham, 2020, pp. 201–214.
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2020 | Conference Paper | LibreCat-ID: 46325
Towards Automated Configuration of Stream Clustering Algorithms
M. Carnein, H. Trautmann, A. Bifet, B. Pfahringer, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19), Würzburg, Germany, 2020, pp. 137–143.
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2020 | Conference Paper | LibreCat-ID: 46321
Inside the tool set of automation: Free social bot code revisited
D. Assenmacher, L. Frischlich , H. Trautmann, C. Grimme, L. Adam, in: C. Grimme, M. Preuß, F. Takes, A. Waldherr (Eds.), Disinformation in Open Online Media, Springer, Wiesbaden, 2020, pp. 101–114.
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2020 | Conference Paper | LibreCat-ID: 46326
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms
M. Carnein, H. Trautmann, A. Bifet, B. Pfahringer, in: Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020), Athens, Greece, 2020, pp. 80–95.
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2020 | Conference Paper | LibreCat-ID: 46324
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection
J. Bossek, P. Kerschke, H. Trautmann, in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), IEEE, Glasgow, UK, 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 46322
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing
J. Bossek, C. Grimme, G. Rudolph, H. Trautmann, in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Glasgow, UK, 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 46323
Dynamic Bi-Objective Routing of Multiple Vehicles
J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), ACM, Cancun, Mexico, 2020, pp. 166–174.
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2020 | Conference Paper | LibreCat-ID: 46327
Automated detection of nostalgic text in the context of societal pessimism
C. Lena, L. Frischlich, H. Trautmann, C. Grimme, in: C. Grimme, M. Preuß, F. Takes, A. Waldherr (Eds.), Disinformation in Open Online Media, Hamburg, Deutschland, 2020, pp. 48–58.
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2020 | Conference Paper | LibreCat-ID: 46330
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M.V. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, 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), Leiden, The Netherlands, 2020, pp. 48–64.
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2020 | Conference Paper | LibreCat-ID: 46329
Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation Tool
D.M. Riehle, M. Niemann, J. Brunk, D. Assenmacher, H. Trautmann, J. Becker, in: G. Meiselwitz (Ed.), Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing, Springer International Publishing, Cham, 2020, pp. 71–86.
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2020 | Conference Paper | LibreCat-ID: 46331
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries
M.V. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 46332
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent
V. Steinhoff, P. Kerschke, P. Aspar, H. Trautmann, C. Grimme, in: Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, 2020, pp. 2445–2452.
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2020 | Conference Paper | LibreCat-ID: 48847
More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization
J. Bossek, F. Neumann, P. Peng, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 1277–1285.
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2020 | Conference Paper | LibreCat-ID: 48849
Evolving Sampling Strategies for One-Shot Optimization Tasks
J. Bossek, C. Doerr, P. Kerschke, A. Neumann, F. Neumann, in: Parallel Problem Solving from Nature (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 111–124.
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2020 | Conference Paper | LibreCat-ID: 48851
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics
J. Bossek, K. Casel, P. Kerschke, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 1286–1294.
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2020 | Conference Paper | LibreCat-ID: 48845
Dynamic Bi-Objective Routing of Multiple Vehicles
J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 166–174.
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2020 | Conference Paper | LibreCat-ID: 48844
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection
J. Bossek, P. Kerschke, H. Trautmann, in: 2020 IEEE Congress on Evolutionary Computation (CEC), IEEE Press, Glasgow, United Kingdom, 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 48850
Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB
J. Bossek, C. Doerr, P. Kerschke, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 778–786.
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2020 | Conference Paper | LibreCat-ID: 48852
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions
J. Bossek, A. Neumann, F. Neumann, in: Parallel Problem Solving from Nature (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 346–359.
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2020 | Conference Paper | LibreCat-ID: 48846
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing
J. Bossek, C. Grimme, G. Rudolph, H. Trautmann, in: 2020 IEEE Congress on Evolutionary Computation (CEC), IEEE Press, Glasgow, United Kingdom, 2020, pp. 1–8.
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2020 | Conference Paper | LibreCat-ID: 48879
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem
A.V. Do, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 681–689.
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2020 | Conference Paper | LibreCat-ID: 48895
Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem
V. Roostapour, J. Bossek, F. Neumann, in: Proceedings of the 2020 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 551–559.
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2020 | Conference Paper | LibreCat-ID: 48897
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: Parallel Problem Solving from {Nature} (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 48–64.
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2019 | Journal Article | LibreCat-ID: 46345
Automated Algorithm Selection: Survey and Perspectives
P. Kerschke, H.H. Hoos, F. Neumann, H. Trautmann, Evolutionary Computation (ECJ) 27 (2019) 3–45.
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2019 | Journal Article | LibreCat-ID: 46344
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms
M. Carnein, H. Trautmann, Business and Information Systems Engineering (BISE) 61 (2019) 277–297.
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2019 | Journal Article | LibreCat-ID: 46346 LibreCat | DOI
 

2019 | Journal Article | LibreCat-ID: 46347
Search Dynamics on Multimodal Multi-Objective Problems
P. Kerschke, H. Wang, M. Preuss, C. Grimme, A. Deutz, H. Trautmann, M. Emmerich, Evolutionary Computation (ECJ) 27 (2019) 577–609.
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2019 | Journal Article | LibreCat-ID: 48877
OpenML: An R Package to Connect to the Machine Learning Platform OpenML
G. Casalicchio, J. Bossek, M. Lang, D. Kirchhoff, P. Kerschke, B. Hofner, H. Seibold, J. Vanschoren, B. Bischl, Computational Statistics 34 (2019) 977–991.
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2019 | Conference Paper | LibreCat-ID: 46338
Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.C.A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, East Lansing, Michigan, USA, 2019, pp. 516–528.
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2019 | Conference Paper | LibreCat-ID: 46343
Multimodality in Multi-Objective Optimization — More Boon than Bane?
C. Grimme, P. Kerschke, H. Trautmann, 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), Springer, East Lansing, MI, USA, 2019, pp. 126–138.
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2019 | Conference Paper | LibreCat-ID: 46339
Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators
J. Bossek, P. Kerschke, A. Neumann, M. Wagner, F. Neumann, H. Trautmann, in: T. Friedrich, C. Doerr, D. Arnold (Eds.), Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV), Potsdam, Germany, 2019, pp. 58–71.
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2019 | Conference Paper | LibreCat-ID: 46337
Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time
J. Bossek, H. Trautmann, in: R. Battiti, M. Brunato, I. Kotsireas, P. Pardalos (Eds.), Learning and Intelligent Optimization, Springer, Cham, 2019, pp. 215–219.
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2019 | Conference Paper | LibreCat-ID: 46340
A Recommender System Based on Omni-Channel Customer Data
M. Carnein, L. Homann, H. Trautmann, G. Vossen, in: Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), Moscow, Russia, 2019, pp. 65–74.
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2019 | Conference Paper | LibreCat-ID: 46341
Customer Segmentation Based on Transactional Data Using Stream Clustering
M. Carnein, H. Trautmann, in: Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), Macau, China, 2019, pp. 280–292.
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2019 | Conference Paper | LibreCat-ID: 46342
Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization
C. Grimme, P. Kerschke, M.T.M. Emmerich, M. Preuss, A.H. Deutz, H. Trautmann, in: AIP Conference Proceedings, AIP Publishing, Leiden, The Netherlands, 2019, pp. 020052-1-020052–4.
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2019 | Conference Paper | LibreCat-ID: 48841
Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, Cham, 2019, pp. 516–528.
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2019 | Conference Paper | LibreCat-ID: 48842
Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators
J. Bossek, P. Kerschke, A. Neumann, M. Wagner, F. Neumann, H. Trautmann, in: Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2019, pp. 58–71.
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2019 | Conference Paper | LibreCat-ID: 48843
Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring
J. Bossek, F. Neumann, P. Peng, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2019, pp. 1443–1451.
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2019 | Conference Paper | LibreCat-ID: 48840
On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem
J. Bossek, C. Grimme, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2019, pp. 516–523.
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2019 | Conference Paper | LibreCat-ID: 48858
Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems
J. Bossek, C. Grimme, in: R. Battiti, M. Brunato, I. Kotsireas, P.M. Pardalos (Eds.), Learning and Intelligent Optimization, Springer International Publishing, Cham, 2019, pp. 184–198.
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2019 | Conference Paper | LibreCat-ID: 48870
Time Complexity Analysis of RLS and (1 + 1) EA for the Edge Coloring Problem
J. Bossek, D. Sudholt, in: Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2019, pp. 102–115.
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2019 | Conference Paper | LibreCat-ID: 48875
Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time
J. Bossek, H. Trautmann, in: R. Battiti, M. Brunato, I. Kotsireas, P.M. Pardalos (Eds.), Learning and Intelligent Optimization, Springer International Publishing, Cham, 2019, pp. 215–219.
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2019 | Book Chapter | LibreCat-ID: 46336
Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-package flacco
P. Kerschke, H. Trautmann, in: N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, M. Vichi (Eds.), Applications in Statistical Computing, Springer, 2019, pp. 93–123.
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2019 | Book | LibreCat-ID: 46335
Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement
H. Trautmann, Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement, Springer International Publishing, 2019.
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2018 | Journal Article | LibreCat-ID: 46351
evoStream — Evolutionary Stream Clustering Utilizing Idle Times
M. Carnein, H. Trautmann, Big Data Research 14 (2018) 101–111.
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2018 | Journal Article | LibreCat-ID: 46353
Multiobjective evolutionary algorithms based on target region preferences
L. Li, Y. Wang, H. Trautmann, N. Jing, M. Emmerich, Swarm and Evolutionary Computation 40 (2018) 196–215.
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