arXiv Machine Learning July 21, 2026 By Gjorgjina Cenikj, Ana Nikolikj, Ga\v{s}per Petelin, Niki van Stein, Carola Doerr, Tome Eftimov

A Survey of Features Used for Representing Black-box Single-objective Continuous Optimization

Read the original on arXiv Machine Learning →

arXiv:2406. 06629v2 Announce Type: replace Abstract: This survey examines key advancements in designing features to represent optimization problem instances, algorithm instances, and their interactions within the context of single-objective continuous black-box optimization.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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