82 citations · 247 across the 54 of their papers we have counts for
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Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Ana Kostovska, Anja Jankovic, Diederick Vermetten +3
Performance complementarity of solvers available to tackle black-box optimization problems gives rise to the important task of algorithm selection (AS). Automated AS approaches can…
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
Ana Nikolikj, Sašo Džeroski, Mario Andrés Muñoz +3
In black-box optimization, it is essential to understand why an algorithm instance works on a set of problem instances while failing on others and provide explanations of its behav…
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms
Ana Kostovska, Diederick Vermetten, Sašo Džeroski +3
Empirical data plays an important role in evolutionary computation research. To make better use of the available data, ontologies have been proposed in the literature to organize t…
RF+clust for Leave-One-Problem-Out Performance Prediction
Ana Nikolikj, Carola Doerr, Tome Eftimov
Per-instance automated algorithm configuration and selection are gaining significant moments in evolutionary computation in recent years. Two crucial, sometimes implicit, ingredien…