Keisuke Onoue

Constraint-Aware Discrete Black-Box Optimization Using Tensor Decomposition

This paper proposes a surrogate modeling approach based on tensor decomposition that captures the structure of discrete search spaces while directly integrating feasibility information and demonstrates that the proposed method improves sample efficiency by effectively guiding the search away from infeasible regions.