Gromov-Wasserstein (GW) distances are generalizations of Gromov-Haussdorff and Wasserstein distances. Due to their invariance under certain distance-preserving transformations they are well suited for many practical applications. In this paper, we introduce a concept of multi-marginal GW transport as well as its regularized and unbalanced versions. Then we generalize a bi-convex relaxation of the GW transport to our multi-marginal setting which is tight if the cost function is conditionally negative definite in a certain sense. The minimization of this relaxed model can be done by an alternating algorithm, where each step can be performed by a Sinkhorn scheme for a multi-marginal transport problem. We show a relation of our multi-marginal GW problem for a tree-structured cost function to an (unbalanced) GW barycenter problem and present different proof-of-concept numerical results.
翻译:Gromov-Wasserstein (GW) 距离是Gromov-Haussdorf和Wasserstein 距离的常规。 由于在某些远距离保护变换下,这些变异性非常适合许多实际应用。 在本文中,我们引入了多边GW运输的概念,以及其正规和不平衡的版本。 然后我们将GW运输的双口松放松到我们的多边际设置上,如果成本功能在某种意义上是有条件的负确定性,那么这种变异性就会很紧。 这种宽松模式的最小化可以通过交替算法来完成, 每一步都可以用辛克霍恩计划来处理多边运输问题。 我们显示了我们多边GW问题与树形成本函数的多边际关系与(不平衡的) GW 巴伊中心问题的关系, 并提出了不同的概念校对数字结果 。