DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis

1 code implementation • 31 Mar 2023 • Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck

We propose DoE2Vec, a variational autoencoder (VAE)-based methodology to learn optimization landscape characteristics for downstream meta-learning tasks, e. g., automated selection of optimization algorithms.

Feature Engineering Meta-Learning