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Moritz Vinzent Seiler
Person information
- affiliation: Paderborn University, Germany
- affiliation (former): University of Münster, Statistics and Optimization, Germany
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2020 – today
- 2024
- [i6]Moritz Vinzent Seiler, Pascal Kerschke, Heike Trautmann
:
Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems. CoRR abs/2401.01192 (2024) - 2023
- [j1]Jonathan Heins
, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann
, Pascal Kerschke
:
A study on the effects of normalized TSP features for automated algorithm selection. Theor. Comput. Sci. 940(Part): 123-145 (2023) - [c10]Moritz Vinzent Seiler, Jeroen Rook
, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, Heike Trautmann
:
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. SSCI 2023: 361-368 - [i5]Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter:
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research. CoRR abs/2301.08525 (2023) - 2022
- [c9]Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke
, Heike Trautmann
:
A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes. GECCO 2022: 657-665 - [c8]Janina Susanne Pohl, Dennis Assenmacher, Moritz Vinzent Seiler, Heike Trautmann, Christian Grimme:
Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. ICWSM Workshops 2022 - [c7]Raphael Patrick Prager
, Moritz Vinzent Seiler
, Heike Trautmann
, Pascal Kerschke
:
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. PPSN (1) 2022: 3-17 - [i4]Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann
:
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes. CoRR abs/2204.05752 (2022) - 2021
- [c6]Jonathan Heins
, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
:
On the potential of normalized TSP features for automated algorithm selection. FOGA 2021: 7:1-7:15 - [c5]Dennis Assenmacher, Marco Niemann, Kilian Müller, Moritz Seiler, Dennis M. Riehle, Heike Trautmann:
RP-Mod&RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets. NeurIPS Datasets and Benchmarks 2021 - [c4]Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke
:
Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization. SSCI 2021: 1-8 - 2020
- [c3]Moritz Seiler, Heike Trautmann
, Pascal Kerschke
:
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries. IJCNN 2020: 1-8 - [c2]Lena Clever
, Dennis Assenmacher
, Kilian Müller
, Moritz Vinzent Seiler
, Dennis M. Riehle
, Mike Preuss
, Christian Grimme
:
FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News. MISDOOM 2020: 218-232 - [c1]Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke
, Heike Trautmann
:
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. PPSN (1) 2020: 48-64 - [i3]Lena Clever, Dennis Assenmacher, Kilian Müller, Moritz Vinzent Seiler, Dennis M. Riehle, Mike Preuss, Christian Grimme:
FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News. CoRR abs/2003.07595 (2020) - [i2]Moritz Seiler, Heike Trautmann, Pascal Kerschke:
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries. CoRR abs/2005.13293 (2020) - [i1]Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann:
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. CoRR abs/2006.15968 (2020)
Coauthor Index
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last updated on 2024-08-05 21:23 CEST by the dblp team
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