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==Applications of Optimal Transport== | ==Applications of Optimal Transport== | ||
* Machine Learning [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024256/ Kolouri, et al, ''Optimal Mass Transport: Signal processing and machine-learning applications''] | * [[Machine Learning]] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024256/ Kolouri, et al, ''Optimal Mass Transport: Signal processing and machine-learning applications''] | ||
==Mathematical Foundations: Optimization== | ==Mathematical Foundations: Optimization== | ||
* Fenchel-Rockafellar and Linear Programming; Brezis (15-17); Rockafellar, ''Variational Analysis'' (505-507) | * Fenchel-Rockafellar and Linear Programming; Brezis (15-17); Rockafellar, ''Variational Analysis'' (505-507) |
Revision as of 01:54, 10 June 2020
Below, you can find a list of new article ideas and suggested references. (Feel free to incorporate additional references! Please list all references you use at the bottom of your article.) If you choose to write about one of these ideas, remove it from the list below and create a new link on the main page.
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The Optimal Transport Problem
- Optimal Transport in one dimension; Villani (73-78); Santambrogio (59-67)
- 1-Wasserstein metric, duality, and measures with unequal mass; Piccoli, Rossi, and Tournus A Wasserstein norm for signed measures, with application to nonlocal transport equation with source term
The 2-Wasserstein Metric
- Displacement convexity; Santambrogio (249-251,271-276); Villani (150-154)
- Asymptotic equivalence of and ; Santambrogio (209-211); Villani (233-235)
Numerical Methods for Optimal Transport
- Semidiscrete Optimal Transport (for ); Santambrogio (242-248); Peyré Cuturi (85-89)
- Computing OT via Benamou-Brenier; Santambrogio (220-225); Peyré, Cuturi (102-108)
- Sliced Wasserstein Distance; Santambrogio (214-215); Peyré, Cuturi (166-169)
- Wasserstein Barycenters; Santambrogio (215-218); Peyré, Cuturi (138-144)
Applications of Optimal Transport
- Machine Learning Kolouri, et al, Optimal Mass Transport: Signal processing and machine-learning applications
Mathematical Foundations: Optimization
- Fenchel-Rockafellar and Linear Programming; Brezis (15-17); Rockafellar, Variational Analysis (505-507)