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Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes.

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

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Towards optimisers that 'Keep Learning'., , , and . GECCO Companion, page 1636-1638. ACM, (2023)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)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)Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes., , , , and . SSCI, page 775-782. IEEE, (2020)Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances., , , and . CoRR, (2024)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)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)Automated algorithm selection for radar network configuration., , , , , and . GECCO, page 1263-1271. ACM, (2022)Expressiveness and robustness of landscape features., , , and . GECCO (Companion), page 2048-2051. ACM, (2019)Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples., and . CoRR, (2024)