Moritz Seiler

14 papers A 2B 1Journal 7Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
LLM Driven Design of Continuous Optimization Problems with Controllable High-level Properties.
CoRR
Urban Skvorc, Niki van Stein, Moritz Seiler, Britta Grimme, Thomas Bäck, Heike Trautmann
2025 A conf
Deep reinforcement learning for instance-specific algorithm configuration.
GECCO
Elias Schede, Moritz Seiler, Kevin Tierney, Heike Trautmann
2025 J jnl
Landscape Features in Single-Objective Continuous Optimization: Have We Hit a Wall in Algorithm Selection Generalization?
CoRR
Gjorgjina Cenikj, Gasper Petelin, Moritz Seiler, Nikola Cenikj, Tome Eftimov
2025 J jnl
Landscape features in single-objective continuous optimization: Have we hit a wall in algorithm selection generalization?
Swarm Evol. Comput.
Gjorgjina Cenikj, Gasper Petelin, Moritz Seiler, Nikola Cenikj, Tome Eftimov
2024 — conf
Learned Features vs. Classical ELA on Affine BBOB Functions.
PPSN (2)
Moritz Seiler, Urban Skvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann
2024 — conf
Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection.
LION
Moritz Seiler, Urban Skvorc, Carola Doerr, Heike Trautmann
2023 J jnl
A study on the effects of normalized TSP features for automated algorithm selection.
Theor. Comput. Sci.
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
2023 J jnl
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.
CoRR
Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter
2021 — conf
<tt>RP-Mod</tt>&<tt>RP-Crowd: </tt> Moderator- and Crowd-Annotated German News Comment Datasets.
NeurIPS Datasets and Benchmarks
Dennis Assenmacher, Marco Niemann, Kilian Müller, Moritz Seiler, Dennis M. Riehle, Heike Trautmann
2021 A conf
On the potential of normalized TSP features for automated algorithm selection.
FOGA
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
2020 — conf
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.
PPSN (1)
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 J jnl
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.
CoRR
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 B conf
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries.
IJCNN
Moritz Seiler, Heike Trautmann, Pascal Kerschke
2020 J jnl
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries.
CoRR
Moritz Seiler, Heike Trautmann, Pascal Kerschke