
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multiobjective Landscapes
Simultaneously visualizing the decision and objective space of continuou...
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Multiobjectivization of Local Search: SingleObjective Optimization Benefits From MultiObjective Gradient Descent
Multimodality is one of the biggest difficulties for optimization as loc...
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Benchmarking in Optimization: Best Practice and Open Issues
This survey compiles ideas and recommendations from more than a dozen re...
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Deep Learning as a Competitive FeatureFree Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
In this work we focus on the wellknown Euclidean Traveling Salesperson ...
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Empirical Study on the Benefits of Multiobjectivization for Solving SingleObjective Problems
When dealing with continuous singleobjective problems, multimodality po...
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One PLOT to Show Them All: Visualization of Efficient Sets in MultiObjective Landscapes
Visualization techniques for the decision space of continuous multiobje...
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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...
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Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection
The TravelingSalespersonProblem (TSP) is arguably one of the bestknow...
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Initial Design Strategies and their Effects on Sequential ModelBased Optimization
Sequential modelbased optimization (SMBO) approaches are algorithms for...
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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...
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OneShot DecisionMaking with and without Surrogates
Oneshot decision making is required in situations in which we can evalu...
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Automated Algorithm Selection: Survey and Perspectives
It has long been observed that for practically any computational problem...
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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...
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Automated Algorithm Selection on Continuous BlackBox Problems By Combining Exploratory Landscape Analysis and Machine Learning
In this paper, we build upon previous work on designing informative and ...
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Comprehensive FeatureBased Landscape Analysis of Continuous and Constrained Optimization Problems Using the RPackage flacco
Choosing the bestperforming optimizer(s) out of a portfolio of optimiza...
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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...
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ASlib: A Benchmark Library for Algorithm Selection
The task of algorithm selection involves choosing an algorithm from a se...
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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...
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Pascal Kerschke
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