AI RESEARCH
SRRM: Improving Recursive Transport Surrogates in the Small-Discrepancy Regime
arXiv CS.LG
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ArXi:2603.18781v1 Announce Type: cross Recursive partitioning methods provide computationally efficient surrogates for the Wasserstein distance, yet their statistical behavior and their resolution in the small-discrepancy regime remain insufficiently understood. We study Recursive Rank Matching (RRM) as a representative instance of this class under a population-anchored reference. In this setting, we establish consistency and an explicit convergence rate for the anchored empirical RRM under the quadratic cost.