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cs.NE2026
On the Structural (Dis)Agreement of Landscape Representations in Black-Box Optimization
Sara Gjorgjieva, Eva Tuba, Barbara Koroušić Seljak +2
Landscape feature representations play a central role in automated algorithm selection and meta-learning for black-box optimization, yet little is known about how different represe…
cs.NE2026
Quantifying the Impact of Modules and Their Interactions in the PSO-X Framework
Christian L. Camacho-Villalón, Ana Nikolikj, Katharina Dost +3
The PSO-X framework incorporates dozens of modules that have been proposed for solving single-objective continuous optimization problems using particle swarm optimization. While mo…
cs.NE2025
Tracing the Interactions of Modular CMA-ES Configurations Across Problem Landscapes
Ana Nikolikj, Mario Andrés Muñoz, Eva Tuba +1
This paper leverages the recently introduced concept of algorithm footprints to investigate the interplay between algorithm configurations and problem characteristics. Performance…