Pascal Kerschke

According to our database, Pascal Kerschke authored at least 65 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• 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

2023

The objective that freed me: a multi-objective local search approach for continuous single-objective optimization.

Pelin Aspar, Vera Steinhoff, Lennart Schäpermeier, Pascal Kerschke, Heike Trautmann, Christian Grimme

Nat. Comput., June, 2023

Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games.

Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar

Appl. Soft Comput., March, 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

Challenges in Benchmarking Optimization Heuristics (Dagstuhl Seminar 23251).

Anne Auger, Peter A. N. Bosman, Pascal Kerschke, Darrell Whitley, Lennart Schäpermeier

Dagstuhl Reports, 2023

Exploratory Landscape Analysis.

Pascal Kerschke, Mike Preuss

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite.

Konstantin Dietrich, Pascal Kerschke

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features.

Raphael Patrick Prager, Konstantin Dietrich, Lennart Schneider, Lennart Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, Olaf Mersmann

Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets.

Lennart Schäpermeier, Pascal Kerschke, Christian Grimme, Heike Trautmann

Proceedings of the Evolutionary Multi-Criterion Optimization, 2023

2022

Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark Problems.

Lennart Schäpermeier, Christian Grimme, Pascal Kerschke

IEEE Trans. Evol. Comput., 2022

Correction to: Estimation of component reliability from superposed renewal processes by means of latent variables.

Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo

Comput. Stat., 2022

Estimation of component reliability from superposed renewal processes by means of latent variables.

Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo

Comput. Stat., 2022

HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.

Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke

CoRR, 2022

HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.

Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke

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

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems.

Jonathan Heins, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, Heike Trautmann

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

Mixture of Decision Trees for Interpretable Machine Learning.

Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 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

MOLE: digging tunnels through multimodal multi-objective landscapes.

Lennart Schäpermeier, Christian Grimme, Pascal Kerschke

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

2021

Lifting the Multimodality-Fog in Continuous Multi-objective Optimization.

Pascal Kerschke, Christian Grimme

Proceedings of the Metaheuristics for Finding Multiple Solutions, 2021

Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization.

Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich

Comput. Oper. Res., 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

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

To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes.

Lennart Schäpermeier, Christian Grimme, Pascal Kerschke

Proceedings of the Evolutionary Multi-Criterion Optimization, 2021

Multi³: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-objective Space by Means of Multiobjectivization.

Pelin Aspar, Pascal Kerschke, Vera Steinhoff, Heike Trautmann, Christian Grimme

Proceedings of the Evolutionary Multi-Criterion Optimization, 2021

2020

Benchmarking in Optimization: Best Practice and Open Issues.

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

CoRR, 2020

Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems.

Vera Steinhoff, Pascal Kerschke, Christian Grimme

CoRR, 2020

Initial Design Strategies and their Effects on Sequential Model-Based Optimization.

Jakob Bossek, Carola Doerr, Pascal Kerschke

CoRR, 2020

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms.

Jakob Bossek, Pascal Kerschke, Heike Trautmann

Appl. Soft Comput., 2020

Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent.

Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis.

Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 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

One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes.

Lennart Schäpermeier, Christian Grimme, Pascal Kerschke

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

Evolving Sampling Strategies for One-Shot Optimization Tasks.

Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann

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

Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB.

Jakob Bossek, Carola Doerr, Pascal Kerschke

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics.

Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.

Jakob Bossek, Pascal Kerschke, Heike Trautmann

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

Search Dynamics on Multimodal Multiobjective Problems.

Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich

Evol. Comput., 2019

Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine Learning.

Pascal Kerschke, Heike Trautmann

Evol. Comput., 2019

Automated Algorithm Selection: Survey and Perspectives.

Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann

Evol. Comput., 2019

OpenML: An R package to connect to the machine learning platform OpenML.

Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl

Comput. Stat., 2019

One-Shot Decision-Making with and without Surrogates.

Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr

CoRR, 2019

Single- and multi-objective game-benchmark for evolutionary algorithms.

Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Exploring the MLDA benchmark on the nevergrad platform.

Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Making a case for (Hyper-)parameter tuning as benchmark problems.

Carola Doerr, Johann Dréo, Pascal Kerschke

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Evolving diverse TSP instances by means of novel and creative mutation operators.

Jakob Bossek, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, Heike Trautmann

Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

Multimodality in Multi-objective Optimization - More Boon than Bane?

Christian Grimme, Pascal Kerschke, Heike Trautmann

Proceedings of the Evolutionary Multi-Criterion Optimization, 2019

2018

Leveraging TSP Solver Complementarity through Machine Learning.

Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann

Evol. Comput., 2018

Workshops at PPSN 2018.

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

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Tutorials at PPSN 2018.

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

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers.

Pascal Kerschke, Jakob Bossek, Heike Trautmann

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017

OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML.

Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl

CoRR, 2017

Exploratory landscape analysis: advanced tutorial at GECCO 2017.

Pascal Kerschke, Mike Preuss

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

flaccogui: exploratory landscape analysis for everyone.

Christian Hanster, Pascal Kerschke

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

An Expedition to Multimodal Multi-objective Optimization Landscapes.

Pascal Kerschke, Christian Grimme

Proceedings of the Evolutionary Multi-Criterion Optimization, 2017

2016

Modelling interventions in INGARCH processes.

Tobias Liboschik, Pascal Kerschke, Konstantinos Fokianos, Roland Fried

Int. J. Comput. Math., 2016

ASlib: A benchmark library for algorithm selection.

Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren

Artif. Intell., 2016

Towards Analyzing Multimodality of Continuous Multiobjective Landscapes.

Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.

Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

The R-Package FLACCO for exploratory landscape analysis with applications to multi-objective optimization problems.

Pascal Kerschke, Heike Trautmann

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015

Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection.

Lars Kotthoff, Pascal Kerschke, Holger H. Hoos, Heike Trautmann

Proceedings of the Learning and Intelligent Optimization - 9th International Conference, 2015

Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms.

Luis Martí, Christian Grimme, Pascal Kerschke, Heike Trautmann, Günter Rudolph

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Detecting Funnel Structures by Means of Exploratory Landscape Analysis.

Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

An Overview of Topic Discovery in Twitter Communication through Social Media Analytics.

Andrey Chinnov, Pascal Kerschke, Christian Meske, Stefan Stieglitz, Heike Trautmann

Proceedings of the 21st Americas Conference on Information Systems, 2015