22 citations · 74 across the 14 of their papers we have counts for
12 papers · 1 filter
Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration
Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj +6
Algorithm selection wizards are effective and versatile tools that automatically select an optimization algorithm given high-level information about the problem and available compu…
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-Aware Optimization Performance Prediction
Risto Trajanov, Stefan Dimeski, Martin Popovski +2
Efficient solving of an unseen optimization problem is related to appropriate selection of an optimization algorithm and its hyper-parameters. For this purpose, automated algorithm…
A Complementarity Analysis of the COCO Benchmark Problems and Artificially Generated Problems
Urban Škvorc, Tome Eftimov, Peter Korošec
When designing a benchmark problem set, it is important to create a set of benchmark problems that are a good generalization of the set of all possible problems. One possible way o…
OPTION: OPTImization Algorithm Benchmarking ONtology
Ana Kostovska, Diederick Vermetten, Carola Doerr +3
Many platforms for benchmarking optimization algorithms offer users the possibility of sharing their experimental data with the purpose of promoting reproducible and reusable resea…