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Ao-Ran Zhang

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#machine learning Preprint Oct 2026

Adaptive Bregman Alternating Projections for Feasible Gromov-Wasserstein Learning

The Gromov-Wasserstein (GW) problem compares structured distributions without requiring a shared feature space or known correspondences, but its nonconvex objective and coupled marginal constraints make computation challenging. Bregman alternating projected gradient (BAPG) uses inexpensive alternating row and column up...

Ao-Ran Zhang, C. Uribe · 0 citations