SRRM: Improving Recursive Transport Surrogates in the Small-Discrepancy Regime
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. We then identify a dominant mismatch mechanism responsible for the loss of resolution in the small-discrepancy regime. Based on this analysis, we introduce Selective Recursive Rank Matching (SRRM), which suppresses the r...
| Authors | Yufei Zhang, Tao Wang, Jingyi Zhang |
|---|---|
| Primary category | stat.ML |
| Published | 19 March 2026 |
| Last updated at source | 19 March 2026 |
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