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45

SCALESPACE
2015
Springer

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A sparse algorithm for dense optimal transport

8 years 21 days ago

A sparse algorithm for dense optimal transport

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Discrete optimal transport solvers do not scale well on dense large problems since they do not explicitly exploit the geometric structure of the cost function. In analogy to continuous optimal transport we provide a framework to verify global optimality of a discrete transport plan locally. This allows construction of a new sparse algorithm to solve large dense problems by considering a sequence of sparse problems instead. Any existing discrete solver can be used as internal black-box. The case of noisy squared Euclidean distance is explicitly detailed. We observe a signiﬁcant reduction of run-time and memory requirements.

Bernhard Schmitzer

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Added	17 Apr 2016
Updated	17 Apr 2016
Type	Journal
Year	2015
Where	SCALESPACE
Authors	Bernhard Schmitzer

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