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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 alternati
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