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ORCIDPascal Kerschke
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- affiliation: TU Dresden, Germany
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2020 – today
- 2024
[c45]Konstantin Dietrich
, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. GECCO 2024- [c44]Jonathan Heins, Lennart Schäpermeier, Pascal Kerschke, Darrell Whitley:
Dancing to the State of the Art? - How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem. PPSN (1) 2024: 100-115 - [c43]Lennart Schäpermeier, Pascal Kerschke:
Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration. PPSN (4) 2024: 202-216 - [d1]Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files. Zenodo, 2024
- [i26]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) - [i25]Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. CoRR abs/2404.07539 (2024) - [i24]Lennart Schäpermeier, Pascal Kerschke:
Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration. CoRR abs/2407.01504 (2024) - [i23]Jonathan Heins, Lennart Schäpermeier, Pascal Kerschke, Darrell Whitley:
Dancing to the State of the Art? How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem. CoRR abs/2407.03927 (2024) - 2023
- [j15]Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar:
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games. Appl. Soft Comput. 136: 110121 (2023) - [j14]Pelin Aspar, Vera Steinhoff, Lennart Schäpermeier, Pascal Kerschke, Heike Trautmann, Christian Grimme:
The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. Nat. Comput. 22(2): 271-285 (2023) - [j13]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) - [c42]Lennart Schäpermeier, Pascal Kerschke, Christian Grimme, Heike Trautmann:
Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. EMO 2023: 291-304 - [c41]Raphael Patrick Prager, Konstantin Dietrich, Lennart Schneider, Lennart Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, Olaf Mersmann:
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. FOGA 2023: 129-139 - [c40]Pascal Kerschke, Mike Preuss:
Exploratory Landscape Analysis. GECCO Companion 2023: 990-1007 - [c39]Konstantin Dietrich, Pascal Kerschke:
Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite. GECCO Companion 2023: 2326-2329 - [i22]Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar:
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games. CoRR abs/2302.08479 (2023) - [i21]Anne Auger, Peter A. N. Bosman, Pascal Kerschke, Darrell Whitley, Lennart Schäpermeier:
Challenges in Benchmarking Optimization Heuristics (Dagstuhl Seminar 23251). Dagstuhl Reports 13(6): 55-80 (2023) - 2022
- [j12]Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo:
Estimation of component reliability from superposed renewal processes by means of latent variables. Comput. Stat. 37(1): 355-379 (2022) - [j11]Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo:
Correction to: Estimation of component reliability from superposed renewal processes by means of latent variables. Comput. Stat. 37(1): 381 (2022) - [j10]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark Problems. IEEE Trans. Evol. Comput. 26(6): 1306-1320 (2022) - [c38]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
MOLE: digging tunnels through multimodal multi-objective landscapes. GECCO 2022: 592-600 - [c37]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 - [c36]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber:
Mixture of Decision Trees for Interpretable Machine Learning. ICMLA 2022: 1175-1182 - [c35]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 - [c34]Jonathan Heins, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, Heike Trautmann:
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. PPSN (1) 2022: 192-206 - [c33]Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke:
HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. PPSN (1) 2022: 575-589 - [e2]Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar:
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13398, Springer 2022, ISBN 978-3-031-14713-5 [contents] - [e1]Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar:
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13399, Springer 2022, ISBN 978-3-031-14720-3 [contents] - [i20]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) - [i19]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
MOLE: Digging Tunnels Through Multimodal Multi-Objective Landscapes. CoRR abs/2204.10848 (2022) - [i18]Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke:
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. CoRR abs/2208.00220 (2022) - [i17]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber:
Mixture of Decision Trees for Interpretable Machine Learning. CoRR abs/2211.14617 (2022) - 2021
- [j9]Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich:
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Comput. Oper. Res. 136: 105489 (2021) - [c32]Pelin Aspar, Pascal Kerschke, Vera Steinhoff, Heike Trautmann, Christian Grimme:
Multi3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-objective Space by Means of Multiobjectivization. EMO 2021: 311-322 - [c31]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes. EMO 2021: 632-644 - [c30]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 - [c29]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 - [p1]Pascal Kerschke, Christian Grimme:
Lifting the Multimodality-Fog in Continuous Multi-objective Optimization. Metaheuristics for Finding Multiple Solutions 2021: 89-111 - 2020
- [j8]Jakob Bossek, Pascal Kerschke, Heike Trautmann:
A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Appl. Soft Comput. 88: 105901 (2020) - [c28]Jakob Bossek, Pascal Kerschke, Heike Trautmann:
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CEC 2020: 1-8 - [c27]Jakob Bossek, Carola Doerr, Pascal Kerschke:
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. GECCO 2020: 778-786 - [c26]Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann:
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics. GECCO 2020: 1286-1294 - [c25]Moritz Seiler, Heike Trautmann, Pascal Kerschke:
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries. IJCNN 2020: 1-8 - [c24]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 - [c23]Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann:
Evolving Sampling Strategies for One-Shot Optimization Tasks. PPSN (1) 2020: 111-124 - [c22]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes. PPSN (2) 2020: 154-167 - [c21]Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke:
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. SSCI 2020: 996-1003 - [c20]Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme:
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent. SSCI 2020: 2445-2452 - [i16]Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann:
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics. CoRR abs/2002.01070 (2020) - [i15]Jakob Bossek, Carola Doerr, Pascal Kerschke:
Initial Design Strategies and their Effects on Sequential Model-Based Optimization. CoRR abs/2003.13826 (2020) - [i14]Jakob Bossek, Pascal Kerschke, Heike Trautmann:
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CoRR abs/2005.13289 (2020) - [i13]Moritz Seiler, Heike Trautmann, Pascal Kerschke:
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries. CoRR abs/2005.13293 (2020) - [i12]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes. CoRR abs/2006.11547 (2020) - [i11]Vera Steinhoff, Pascal Kerschke, Christian Grimme:
Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems. CoRR abs/2006.14423 (2020) - [i10]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) - [i9]Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise:
Benchmarking in Optimization: Best Practice and Open Issues. CoRR abs/2007.03488 (2020) - [i8]Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme:
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent. CoRR abs/2010.01004 (2020) - [i7]Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes. CoRR abs/2011.14395 (2020)
2010 – 2019
- 2019
- [j7]Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl:
OpenML: An R package to connect to the machine learning platform OpenML. Comput. Stat. 34(3): 977-991 (2019) - [j6]Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann:
Automated Algorithm Selection: Survey and Perspectives. Evol. Comput. 27(1): 3-45 (2019) - [j5]Pascal Kerschke, Heike Trautmann:
Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine Learning. Evol. Comput. 27(1): 99-127 (2019) - [j4]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich:
Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. 27(4): 577-609 (2019) - [c19]Christian Grimme, Pascal Kerschke, Heike Trautmann:
Multimodality in Multi-objective Optimization - More Boon than Bane? EMO 2019: 126-138 - [c18]Jakob Bossek, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, Heike Trautmann:
Evolving diverse TSP instances by means of novel and creative mutation operators. FOGA 2019: 58-71 - [c17]Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar:
Single- and multi-objective game-benchmark for evolutionary algorithms. GECCO 2019: 647-655 - [c16]Pascal Kerschke, Mike Preuss:
Exploratory landscape analysis. GECCO (Companion) 2019: 1137-1155 - [c15]Carola Doerr, Johann Dréo, Pascal Kerschke:
Making a case for (Hyper-)parameter tuning as benchmark problems. GECCO (Companion) 2019: 1755-1764 - [c14]Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud:
Exploring the MLDA benchmark on the nevergrad platform. GECCO (Companion) 2019: 1888-1896 - [i6]Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr:
One-Shot Decision-Making with and without Surrogates. CoRR abs/1912.08956 (2019) - 2018
- [j3]Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann:
Leveraging TSP Solver Complementarity through Machine Learning. Evol. Comput. 26(4) (2018) - [c13]Pascal Kerschke, Jakob Bossek, Heike Trautmann:
Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers. GECCO (Companion) 2018: 1737-1744 - [c12]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [c11]Robin C. Purshouse, Christine Zarges, Sylvain Cussat-Blanc, Michael G. Epitropakis, Marcus Gallagher, Thomas Jansen, Pascal Kerschke, Xiaodong Li, Fernando G. Lobo, Julian F. Miller, Pietro S. Oliveto, Mike Preuss, Giovanni Squillero, Alberto Paolo Tonda, Markus Wagner, Thomas Weise, Dennis Wilson, Borys Wróbel, Ales Zamuda:
Workshops at PPSN 2018. PPSN (2) 2018: 490-497 - [i5]Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann:
Automated Algorithm Selection: Survey and Perspectives. CoRR abs/1811.11597 (2018) - 2017
- [c10]Pascal Kerschke, Christian Grimme:
An Expedition to Multimodal Multi-objective Optimization Landscapes. EMO 2017: 329-343 - [c9]Pascal Kerschke, Mike Preuss:
Exploratory landscape analysis: advanced tutorial at GECCO 2017. GECCO (Companion) 2017: 762-781 - [c8]Christian Hanster, Pascal Kerschke:
flaccogui: exploratory landscape analysis for everyone. GECCO (Companion) 2017: 1215-1222 - [i4]Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl:
OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. CoRR abs/1701.01293 (2017) - [i3]Pascal Kerschke, Heike Trautmann:
Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning. CoRR abs/1711.08921 (2017) - 2016
- [j2]Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren:
ASlib: A benchmark library for algorithm selection. Artif. Intell. 237: 41-58 (2016) - [j1]Tobias Liboschik, Pascal Kerschke, Konstantinos Fokianos, Roland Fried:
Modelling interventions in INGARCH processes. Int. J. Comput. Math. 93(4): 640-657 (2016) - [c7]Pascal Kerschke, Heike Trautmann:
The R-Package FLACCO for exploratory landscape analysis with applications to multi-objective optimization problems. CEC 2016: 5262-5269 - [c6]Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann:
Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. GECCO 2016: 229-236 - [c5]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich:
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN 2016: 962-972 - 2015
- [c4]Andrey Chinnov, Pascal Kerschke, Christian Meske, Stefan Stieglitz, Heike Trautmann:
An Overview of Topic Discovery in Twitter Communication through Social Media Analytics. AMCIS 2015 - [c3]Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann:
Detecting Funnel Structures by Means of Exploratory Landscape Analysis. GECCO 2015: 265-272 - [c2]Luis Martí, Christian Grimme, Pascal Kerschke, Heike Trautmann, Günter Rudolph:
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms. GECCO (Companion) 2015: 1427-1428 - [c1]Lars Kotthoff, Pascal Kerschke, Holger H. Hoos, Heike Trautmann:
Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection. LION 2015: 202-217 - [i2]Luis Martí, Christian Grimme, Pascal Kerschke, Heike Trautmann, Günter Rudolph:
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms. CoRR abs/1503.07845 (2015) - [i1]Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren:
ASlib: A Benchmark Library for Algorithm Selection. CoRR abs/1506.02465 (2015)
Coauthor Index
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