21 citations · 54 across the 10 of their papers we have counts for
3 papers · 1 filter
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison
Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht +3
Fair algorithm evaluation is conditioned on the existence of high-quality benchmark datasets that are non-redundant and are representative of typical optimization scenarios. In thi…
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
Ana Kostovska, Diederick Vermetten, Sašo Džeroski +3
Selecting the most suitable algorithm and determining its hyperparameters for a given optimization problem is a challenging task. Accurately predicting how well a certain algorithm…
Explainable Landscape Analysis in Automated Algorithm Performance Prediction
Risto Trajanov, Stefan Dimeski, Martin Popovski +2
Predicting the performance of an optimization algorithm on a new problem instance is crucial in order to select the most appropriate algorithm for solving that problem instance. Fo…