Analyzing Flexible Search Distributions in Black-Box Optimization with Normalizing Flow-based Estimation of Distribution Algorithms
This work proposes NF-EDA, a Normalizing Flow-based Estimation of Distribution Algorithm that replaces fixed Gaussian models with a learned, flexible search distribution, and highlights the importance of flexible search distributions for understanding and improving model-based black-box optimization.