Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy

19 Jun 2020Quentin RenauCarola DoerrJohann DreoBenjamin Doerr

Exploratory landscape analysis (ELA) supports supervised learning approaches for automated algorithm selection and configuration by providing sets of features that quantify the most relevant characteristics of the optimization problem at hand. In black-box optimization, where an explicit problem representation is not available, the feature values need to be approximated from a small number of sample points... (read more)

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