12 Publications

Mark all

[12]
2024 | Conference Paper | LibreCat-ID: 54643
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.
LibreCat
 
[11]
2024 | Conference Paper | LibreCat-ID: 52749
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.
LibreCat | DOI
 
[10]
2023 | Journal Article | LibreCat-ID: 46310
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 | DOI
 
[9]
2023 | Conference Paper | LibreCat-ID: 48898
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), n.d., pp. 361–368.
LibreCat | DOI
 
[8]
2022 | Conference Paper | LibreCat-ID: 46307
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
M. 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 | DOI
 
[7]
2022 | Conference Paper | LibreCat-ID: 46304
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods
R.P. Prager, M. Seiler, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.
LibreCat | DOI
 
[6]
2022 | Conference Paper | LibreCat-ID: 46303
Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches
J.S. Pohl, D. Assenmacher, M. 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 | DOI
 
[5]
2021 | Conference Paper | LibreCat-ID: 46315
Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization
R.P. Prager, M. Seiler, H. Trautmann, P. Kerschke, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021, pp. 1–8.
LibreCat | DOI
 
[4]
2021 | Conference Paper | LibreCat-ID: 46312
RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets
D. Assenmacher, M. Niemann, K. Müller, M. Seiler, D.M. Riehle, H. Trautmann, in: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), Virtual Event, 2021, pp. 1–14.
LibreCat
 
[3]
2021 | Conference Paper | LibreCat-ID: 46313
On the Potential of Normalized TSP Features for Automated Algorithm Selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: for Computing Machinery Association (Ed.), Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA XVI), Association for Computing Machinery, Dornbirn, Austria, 2021, pp. 1–15.
LibreCat | DOI
 
[2]
2020 | Conference Paper | LibreCat-ID: 46331
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries
M. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1–8.
LibreCat | DOI
 
[1]
2020 | Conference Paper | LibreCat-ID: 46330
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, H. Trautmann (Eds.), Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, The Netherlands, 2020, pp. 48–64.
LibreCat | DOI
 

Search

Filter Publications

Display / Sort

Export / Embed

12 Publications

Mark all

[12]
2024 | Conference Paper | LibreCat-ID: 54643
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.
LibreCat
 
[11]
2024 | Conference Paper | LibreCat-ID: 52749
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.
LibreCat | DOI
 
[10]
2023 | Journal Article | LibreCat-ID: 46310
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 | DOI
 
[9]
2023 | Conference Paper | LibreCat-ID: 48898
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), n.d., pp. 361–368.
LibreCat | DOI
 
[8]
2022 | Conference Paper | LibreCat-ID: 46307
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
M. 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 | DOI
 
[7]
2022 | Conference Paper | LibreCat-ID: 46304
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods
R.P. Prager, M. Seiler, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.
LibreCat | DOI
 
[6]
2022 | Conference Paper | LibreCat-ID: 46303
Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches
J.S. Pohl, D. Assenmacher, M. 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 | DOI
 
[5]
2021 | Conference Paper | LibreCat-ID: 46315
Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization
R.P. Prager, M. Seiler, H. Trautmann, P. Kerschke, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021, pp. 1–8.
LibreCat | DOI
 
[4]
2021 | Conference Paper | LibreCat-ID: 46312
RP-Mod & RP-Crowd: Moderator- and Crowd-Annotated German News Comment Datasets
D. Assenmacher, M. Niemann, K. Müller, M. Seiler, D.M. Riehle, H. Trautmann, in: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021), Virtual Event, 2021, pp. 1–14.
LibreCat
 
[3]
2021 | Conference Paper | LibreCat-ID: 46313
On the Potential of Normalized TSP Features for Automated Algorithm Selection
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: for Computing Machinery Association (Ed.), Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA XVI), Association for Computing Machinery, Dornbirn, Austria, 2021, pp. 1–15.
LibreCat | DOI
 
[2]
2020 | Conference Paper | LibreCat-ID: 46331
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries
M. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1–8.
LibreCat | DOI
 
[1]
2020 | Conference Paper | LibreCat-ID: 46330
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, H. Trautmann (Eds.), Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, The Netherlands, 2020, pp. 48–64.
LibreCat | DOI
 

Search

Filter Publications

Display / Sort

Export / Embed