Jin-Tao He

NeurGO: Learning to Generate Elite Candidates for Meta-Black-Box Expensive Optimization

This work proposes NeurGO, a generative MetaBBO framework that directly synthesizes elite candidates from historical population states and designs a quality-diversity loss to maintain solution quality and population diversity throughout the search.