- E-Mail:
- moritz.seiler@uni-paderborn.de
- Telefon:
- +49 5251 60-6311
- Büroanschrift:
-
Fürstenallee 11
33102 Paderborn - Raum:
- FU.227
Publikationen
Aktuelle Publikationen
Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems
M. Seiler, P. Kerschke, H. Trautmann, Evolutionary Computation (2025) 1–27.
RandOptGen: A Unified Random Problem Generator for Single- and Multi-Objective Optimization Problems with Mixed-Variable Input Spaces
M. Seiler, O.L. Preuß, H. Trautmann, in: B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, ACM, 2025, pp. 76–84.
Deep reinforcement learning for instance-specific algorithm configuration (GECCO Best Paper Award)
E. Schede, M. Seiler, K. Tierney, H. Trautmann, in: B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, ACM, 2025, pp. 1190–1198.
Learned Features vs. Classical ELA on Affine BBOB Functions
M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, H. Trautmann, in: M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tušar, P. Machado, T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII, Springer International Publishing, Cham, 2024, pp. 1–14.
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP
M. 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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