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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.