Moritz Vinzent Seiler

According to our database, Moritz Vinzent Seiler authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems.

Moritz Vinzent Seiler, Pascal Kerschke, Heike Trautmann

CoRR, 2024

Learned Features vs. Classical ELA on Affine BBOB Functions.

Moritz Seiler, Urban Skvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

2023

A study on the effects of normalized TSP features for automated algorithm selection.

Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke

Theor. Comput. Sci., 2023

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.

Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter

CoRR, 2023

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.

Moritz Vinzent Seiler, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, Heike Trautmann

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022

Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods.

Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches.

Janina Susanne Pohl, Dennis Assenmacher, Moritz Vinzent Seiler, Heike Trautmann, Christian Grimme

Proceedings of the Workshop Proceedings of the 16th International AAAI Conference on Web and Social Media, 2022

A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes.

Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2021

Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization.

Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

<tt>RP-Mod</tt>&<tt>RP-Crowd: </tt> Moderator- and Crowd-Annotated German News Comment Datasets.

Dennis Assenmacher, Marco Niemann, Kilian Müller, Moritz Seiler, Dennis M. Riehle, Heike Trautmann

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

On the potential of normalized TSP features for automated algorithm selection.

Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.

Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News.

Lena Clever, Dennis Assenmacher, Kilian Müller, Moritz Vinzent Seiler, Dennis M. Riehle, Mike Preuss, Christian Grimme

Proceedings of the Disinformation in Open Online Media, 2020

Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries.

Moritz Seiler, Heike Trautmann, Pascal Kerschke

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020