Probabilistic Inverse Optimal Transport

• URL: http://arxiv.org/abs/2112.09754v1
• Date: Fri, 17 Dec 2021 20:33:27 GMT
• Title: Probabilistic Inverse Optimal Transport
• Authors: Wei-Ting Chiu, Pei Wang, Patrick Shafto
• Abstract summary: Optimal transport (OT) formalizes the problem of finding an optimal coupling between probability measures given a cost matrix. The inverse problem of inferring the cost given a coupling is Inverse Optimal Transport (IOT) We formalize and systematically analyze the properties of IOT using tools from the study of entropy-regularized OT.
• Score: 11.425633112192521
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Optimal transport (OT) formalizes the problem of finding an optimal coupling between probability measures given a cost matrix. The inverse problem of inferring the cost given a coupling is Inverse Optimal Transport (IOT). IOT is less well understood than OT. We formalize and systematically analyze the properties of IOT using tools from the study of entropy-regularized OT. Theoretical contributions include characterization of the manifold of cross-ratio equivalent costs, the implications of model priors, and derivation of an MCMC sampler. Empirical contributions include visualizations of cross-ratio equivalent effect on basic examples and simulations validating theoretical results.

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