2 papers
cs.AI2026
Synthesizing Feature Extractors: An Agentic Approach for Algorithm Selection
Hai Xia, Carlos Ansótegui, Stefan Szeider
Algorithm selection for constraint satisfaction problems requires extracting features that capture problem structure. Manually designing feature extractors demands deep domain expe…
cs.LG2021
Learning How to Optimize Black-Box Functions With Extreme Limits on the Number of Function Evaluations
Carlos Ansotegui, Meinolf Sellmann, Tapan Shah +1
We consider black-box optimization in which only an extremely limited number of function evaluations, on the order of around 100, are affordable and the function evaluations must b…