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Optimal Transport with Proximal Splitting
Open accessAbstract
This article reviews the use of first order convex optimization schemes to solve the discretized dynamic optimal transport problem, initially proposed by Benamou and Brenier. We develop a staggered grid discretization that is well adapted to the computation of the $L^2$ optimal transport geodesic between distributions defined on a uniform spatial grid. We show how proximal splitting schemes can be used to solve the resulting large scale convex optimization problem. A specific instantiation of this method on a centered grid corresponds to the initial algorithm developed by Benamou and Brenier. We also show how more general cost functions can be taken into account and how to extend the method to perform optimal transport on a Riemannian manifold.
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Cites
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
The Hungarian method for the assignment problem
Kuhn, H. W. (1955) · Naval Research Logistics Quarterly · doi:10.1002/nav.3800020109 · Cited by 13,120
Cited by
Computational Optimal Transport
Peyré, G., & Cuturi, M. (2019) · now publishers, Inc. eBooks · doi:10.1561/9781680835519 · Cited by 847
Self-citationKomodakis, N., & Pesquet, J.-C. (2015) · IEEE Signal Processing Magazine · doi:10.1109/msp.2014.2377273 · Cited by 419
Scaling algorithms for unbalanced optimal transport problems
Chizat, L., Peyré, G., Schmitzer, B., & Vialard, F.-X. (2018) · Mathematics of Computation · doi:10.1090/mcom/3303 · Cited by 336
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Metadata
- Authors
- Papadakis, N., Peyré, G., & Oudet, E.
- Venue
- SIAM Journal on Imaging Sciences
- Published
- 2014-01
- Volume
- 7
- Issue
- 1
- Pages
- 212-238
- ISSN
- 1936-4954 (ISSN-L)
- OpenAlex
- W2028852533
- Cited by
- 178
- References
- 2
- FWCI
- 35.49
- Type
- journal article
- Language
- en
- Open access
- green
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