arXiv · 1906.00616
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
Abstract
In this paper, we address the problem of Domain Adaptation (DA) using Optimal Transport (OT) on Riemannian manifolds. We model the difference between two domains by a diffeomorphism and use the polar factorization theorem to claim that OT is indeed optimal for DA in a well-defined sense, up to a volume preserving map. We then focus on the manifold of Symmetric and Positive-Definite (SPD) matrices, whose structure provided a useful context in recent applications. We demonstrate the polar factorization theorem on this manifold. Due to the uniqueness of the weighted Riemannian mean, and by exploiting existing regularized OT algorithms, we formulate a simple algorithm that maps the source domain to the target domain. We test our algorithm on two Brain-Computer Interface (BCI) data sets and observe state of the art performance.
Explore related subjects
Keep this discovery
Or Yair, Felix Dietrich, Ronen Talmon, Ioannis G. Kevrekidis. 2019-06-03. Domain Adaptation with Optimal Transport on the Manifold of SPD matrices. https://arxiv.org/abs/1906.00616
Cite the original work for its findings. Save a collection to share your selection of sources.