Convergence rate of entropy-regularized multi-marginal optimal transport costs
arXiv:2307.03023 · doi:10.4153/S0008414X24000257
Abstract
We investigate the convergence rate of multi-marginal optimal transport costs that are regularized with the Boltzmann-Shannon entropy, as the noise parameter tends to . We establish lower and upper bounds on the difference with the unregularized cost of the form for some explicit dimensional constants depending on the marginals and on the ground cost, but not on the optimal transport plans themselves. Upper bounds are obtained for Lipschitz costs or locally semi-concave costs for a finer estimate, and lower bounds for costs satisfying some signature condition on the mixed second derivatives that may include degenerate costs, thus generalizing results previously in the two marginals case and for non-degenerate costs. We obtain in particular matching bounds in some typical situations where the optimal plan is deterministic.
References in corpus (7)
- Optimal-transport formulation of electronic density-functional theory
- Optimal transportation for the determinant
- The Multimarginal Optimal Transport Formulation of Adversarial Multiclass Classification
- Monge solutions and uniqueness in multi-marginal optimal transport via graph theory
- Stability of Schrödinger Potentials and Convergence of Sinkhorn's Algorithm
- Robust risk management via multi-marginal optimal transport
- On the Convergence Rate of Sinkhorn's Algorithm