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.
LibreCat: /record/52759
DOI: 10.1007/978-3-031-56852-7_20

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.
LibreCat: /record/52749
DOI: 10.1109/ssci52147.2023.10372008

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.
LibreCat: /record/47522
DOI: 10.1145/3594805.3607136

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.
LibreCat: /record/46297

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.
LibreCat: /record/46298

Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python
R.P. Prager, H. Trautmann, Evolutionary Computation (2023) 1–25.
LibreCat: /record/46299
DOI: 10.1162/evco_a_00341

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.
LibreCat: /record/46310
DOI: https://doi.org/10.1016/j.tcs.2022.10.019

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.
LibreCat: /record/52530
DOI: 10.1145/3583133.3590757

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.
LibreCat: /record/48898
DOI: 10.1109/SSCI52147.2023.10372008

(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.
LibreCat: /record/46300
DOI: 10.1007/978-3-658-35658-3_13

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.
LibreCat: /record/46301
DOI: 10.1007/978-3-031-21743-2_1

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.
LibreCat: /record/46316
DOI: 10.1177/08944393211012268

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. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 575–589.
LibreCat: /record/46306
DOI: 10.1007/978-3-031-14714-2_40

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.
LibreCat: /record/46307
DOI: 10.1145/3512290.3528834

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. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.
LibreCat: /record/46304
DOI: 10.1007/978-3-031-14714-2_1

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.
LibreCat: /record/46303
DOI: 10.36190/2022.91

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.
LibreCat: /record/46305
DOI: 10.1145/3520304.3528998

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.
LibreCat: /record/46309
DOI: 10.3390/app12189094

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.
LibreCat: /record/46308
DOI: 10.1007/s11047-022-09919-w

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. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 192–206.
LibreCat: /record/46302