Adaptive Bregman Alternating Projections for Feasible Gromov-Wasserstein Learning
cs.LG, cs.CG, math.OC
Submitted: 2026-10-03
Updated: 2026-10-03
Sources
- Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms
- Annealed Sinkhorn for Optimal Transport: convergence, regularization path and debiasing
- A review of matrix scaling and Sinkhorn's normal form for matrices and positive maps
- A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport
- TUDataset: A collection of benchmark datasets for learning with graphs
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