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Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes.

, , , , and . SSCI, page 775-782. IEEE, (2020)

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Exploratory Landscape Analysis Feature Values for the 24 Noiseless BBOB Functions., , , and . (January 2021)Towards optimisers that 'Keep Learning'., , , and . GECCO Companion, page 1636-1638. ACM, (2023)Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy., , , and . PPSN (2), volume 12270 of Lecture Notes in Computer Science, page 139-153. Springer, (2020)Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions., , , and . EvoApplications, volume 12694 of Lecture Notes in Computer Science, page 17-33. Springer, (2021)Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes., , , , and . SSCI, page 775-782. IEEE, (2020)Expressiveness and robustness of landscape features., , , and . GECCO (Companion), page 2048-2051. ACM, (2019)Landscape-Aware Selection of Metaheuristics for the Optimization of Radar Networks. (Sélection de Métaheuriques Guidée par le Paysage de Recherche pour l'Optimisation de Réseaux de Radars).. Polytechnic Institute of Paris, Palaiseau, France, (2022)Automated algorithm selection for radar network configuration., , , , , and . GECCO, page 1263-1271. ACM, (2022)On the Utility of Probing Trajectories for Algorithm-Selection., and . EvoApplications@EvoStar, volume 14634 of Lecture Notes in Computer Science, page 98-114. Springer, (2024)Experimental Data Set for the study "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy"., , , and . (June 2020)