43 citations · 98 across the 13 of their papers we have counts for
15 papers
Sampling on Random Subspaces under Limited Data in the Context of Exploratory Landscape Analysis
Iván Olarte Rodríguez, Anja Jankovic, Thomas Bäck +1
Classical space-filling designs often fail to provide reliable statistical results for Exploratory Landscape Analysis (ELA) when only limited evaluation budgets are available, as c…
Improving Evaluation of Recombination-based Cartesian Genetic Programming
Duy Long Tran, Anja Jankovic, Marie Anastacio +2
Cartesian Genetic Programming has traditionally been using mutation as its main and often sole genetic operator to drive evolutionary search. Despite advancements in recent years,…
Does Dimensionality Reduction via Random Projections Preserve Landscape Features?
Iván Olarte Rodríguez, Anja Jankovic, Thomas Bäck +1
Exploratory Landscape Analysis (ELA) provides numerical features for characterizing black-box optimization problems. In high-dimensional settings, however, ELA suffers from sparsit…
TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming
Roman Kalkreuth, Fabricio Olivetti de França, Julian Dierkes +4
Over the years, genetic programming (GP) has evolved, with many proposed variations, especially in how they represent a solution. Being essentially a program synthesis algorithm, i…
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization
Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten +6
The performance of automated algorithm selection (AAS) strongly depends on the portfolio of algorithms to choose from. Selecting the portfolio is a non-trivial task that requires b…
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…