Reliable Sample-Level Quantum Error Mitigation via Dominance-Aware Clustering
It is shown that nearest-center assignment, as used in clustering algorithms such as the $k$-modes algorithm, can fail to produce dominated regions even when the true centers are known, which motivates responsibility thresholding and a local dominance screen, whose combination is called dominance-aware (DA) refinement.