Subspace Detours Meet Gromov-Wasserstein

被引:2
作者
Bonet, Clement [1 ]
Vayer, Titouan [2 ]
Courty, Nicolas [3 ]
Septier, Francois [1 ]
Drumetz, Lucas [4 ]
机构
[1] Univ Bretagne Sud, CNRS, UMR 6205, Lab Math Bretagne Atlantique, F-56000 Vannes, France
[2] CNRS, UMR 5668, ENS Lyon, LIP, F-69342 Lyon, France
[3] Univ Bretagne Sud, Dept Comp Sci, CNRS, IRISA,UMR 6074, F-56000 Vannes, France
[4] CNRS, IMT Atlantique, UMR 6285, Lab STICC, F-29238 Brest, France
关键词
optimal transport; Gromov-Wasserstein; subspace detours; Knothe-Rosenblatt;
D O I
10.3390/a14120366
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the context of optimal transport (OT) methods, the subspace detour approach was recently proposed by Muzellec and Cuturi. It consists of first finding an optimal plan between the measures projected on a wisely chosen subspace and then completing it in a nearly optimal transport plan on the whole space. The contribution of this paper is to extend this category of methods to the Gromov-Wasserstein problem, which is a particular type of OT distance involving the specific geometry of each distribution. After deriving the associated formalism and properties, we give an experimental illustration on a shape matching problem. We also discuss a specific cost for which we can show connections with the Knothe-Rosenblatt rearrangement.
引用
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页数:29
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