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


Nov 29, 2020
Lennart Sch├Ąpermeier, Christian Grimme, Pascal Kerschke

* This version has been accepted for publication at the 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2021) 

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


Oct 02, 2020
Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme

* This version has been accepted for publication at the IEEE Symposium Series on Computational Intelligence (IEEE SSCI) 2020 

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Benchmarking in Optimization: Best Practice and Open Issues


Jul 07, 2020
Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel Lopez-Ibanez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise


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


Jun 29, 2020
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann

* This version has been accepted for publication at the Parallel Problem Solving from Nature (PPSN) 2020 

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


Jun 25, 2020
Vera Steinhoff, Pascal Kerschke, Christian Grimme


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


Jun 20, 2020
Lennart Sch├Ąpermeier, Christian Grimme, Pascal Kerschke

* This version has been accepted for publication at the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI) 

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Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries


May 27, 2020
Moritz Seiler, Heike Trautmann, Pascal Kerschke

* This version has been accepted for publication at the International Joint Conference on Neural Networks (IJCNN) 2020, which is part of the IEEE World Congress on Computational Intelligence (IEEE WCCI) 2020 

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


May 27, 2020
Jakob Bossek, Pascal Kerschke, Heike Trautmann

* This version has been accepted for publication at the IEEE Congress on Evolutionary Computation (IEEE CEC) 2020, which is part of the IEEE World Congress on Computational Intelligence (IEEE WCCI) 2020 

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


Mar 30, 2020
Jakob Bossek, Carola Doerr, Pascal Kerschke

* To appear in Proc. of ACM Genetic and Evolutionary Computation Conference (GECCO'20) 

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The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics


Feb 04, 2020
Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann


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One-Shot Decision-Making with and without Surrogates


Dec 20, 2019
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr


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One-Sh ot Decision-Making with and without Surrogates


Dec 19, 2019
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr


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Automated Algorithm Selection: Survey and Perspectives


Nov 28, 2018
Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann

* This is the author's final version, and the article has been accepted for publication in Evolutionary Computation 

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


Nov 24, 2017
Pascal Kerschke, Heike Trautmann


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Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco


Aug 17, 2017
Pascal Kerschke

* 30 pages, 15 figures, currently under review at Journal of Statistical Software, further information on flacco can be found here: https://github.com/kerschke/flacco 

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


May 04, 2017
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl


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ASlib: A Benchmark Library for Algorithm Selection


Apr 06, 2016
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Frechette, Holger Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren

* Accepted to be published in Artificial Intelligence Journal 

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


Mar 26, 2015
Luis Marti, Christian Grimme, Pascal Kerschke, Heike Trautmann, G├╝nter Rudolph

* 13 pages 

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