Pascal Kerschke

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University of Münster

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

Simultaneously visualizing the decision and objective space of continuou...
11/29/2020 ∙ by Lennart Schäpermeier, et al. ∙ 16 ∙ share

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

Multimodality is one of the biggest difficulties for optimization as loc...
10/02/2020 ∙ by Vera Steinhoff, et al. ∙ 10 ∙ share

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Benchmarking in Optimization: Best Practice and Open Issues

This survey compiles ideas and recommendations from more than a dozen re...
07/07/2020 ∙ by Thomas Bartz-Beielstein, et al. ∙ 11 ∙ share

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

In this work we focus on the well-known Euclidean Traveling Salesperson ...
06/29/2020 ∙ by Moritz Seiler, et al. ∙ 9 ∙ share

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

When dealing with continuous single-objective problems, multimodality po...
06/25/2020 ∙ by Vera Steinhoff, et al. ∙ 4 ∙ share

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

Visualization techniques for the decision space of continuous multi-obje...
06/20/2020 ∙ by Lennart Schäpermeier, et al. ∙ 15 ∙ share

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Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries

Artificial neural networks in general and deep learning networks in part...
05/27/2020 ∙ by Moritz Seiler, et al. ∙ 46 ∙ share

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

The Traveling-Salesperson-Problem (TSP) is arguably one of the best-know...
05/27/2020 ∙ by Jakob Bossek, et al. ∙ 5 ∙ share

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

Sequential model-based optimization (SMBO) approaches are algorithms for...
03/30/2020 ∙ by Jakob Bossek, et al. ∙ 3 ∙ share

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

Several important optimization problems in the area of vehicle routing c...
02/04/2020 ∙ by Jakob Bossek, et al. ∙ 2 ∙ share

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One-Shot Decision-Making with and without Surrogates

One-shot decision making is required in situations in which we can evalu...
12/19/2019 ∙ by Jakob Bossek, et al. ∙ 20 ∙ share

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Automated Algorithm Selection: Survey and Perspectives

It has long been observed that for practically any computational problem...
11/28/2018 ∙ by Pascal Kerschke, et al. ∙ 2 ∙ share

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Estimation of component reliability in repairable series systems with masked cause of failure by means of latent variables

In this work, we propose two methods, a Bayesian and a maximum likelihoo...
06/20/2018 ∙ by Agatha Rodrigues, et al. ∙ 0 ∙ share

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

In this paper, we build upon previous work on designing informative and ...
11/24/2017 ∙ by Pascal Kerschke, et al. ∙ 0 ∙ share

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

Choosing the best-performing optimizer(s) out of a portfolio of optimiza...
08/17/2017 ∙ by Pascal Kerschke, et al. ∙ 0 ∙ share

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

OpenML is an online machine learning platform where researchers can easi...
01/05/2017 ∙ by Giuseppe Casalicchio, et al. ∙ 0 ∙ share

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ASlib: A Benchmark Library for Algorithm Selection

The task of algorithm selection involves choosing an algorithm from a se...
06/08/2015 ∙ by Bernd Bischl, et al. ∙ 0 ∙ share

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

In the a posteriori approach of multiobjective optimization the Pareto f...
03/26/2015 ∙ by Luis Marti, et al. ∙ 0 ∙ share

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