نسخة أولية وصول مفتوح
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 …