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Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal Transport (2110.12678v2)

Published 25 Oct 2021 in cs.AI, cs.NA, math.NA, math.ST, and stat.TH

Abstract: We derive nearly tight and non-asymptotic convergence bounds for solutions of entropic semi-discrete optimal transport. These bounds quantify the stability of the dual solutions of the regularized problem (sometimes called Sinkhorn potentials) w.r.t. the regularization parameter, for which we ensure a better than Lipschitz dependence. Such facts may be a first step towards a mathematical justification of annealing or $\varepsilon$-scaling heuristics for the numerical resolution of regularized semi-discrete optimal transport. Our results also entail a non-asymptotic and tight expansion of the difference between the entropic and the unregularized costs.

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