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Multi-scale algorithms for optimal transport

Abstract: 

Optimal transport is a geometrically intuitive and robust way to quantify differences between probability measures.
It is becoming increasingly popular as numerical tool in image processing, computer vision and machine learning.
A key challenge is its efficient computation, in particular on large problems. Various algorithms exist, tailored to different special cases.
Multi-scale methods can be applied to classical discrete algorithms, as well as entropy regularization techniques. They provide a good compromise between efficiency and flexibility.

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Paper Details

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Submitted On:
2 June 2018 - 2:58am
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Type:
Presentation Slides
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Presenter's Name:
Bernhard Schmitzer
Paper Code:
1094
Document Year:
2018
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schmitzer_2018-06_Lausanne.pdf

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[1] , "Multi-scale algorithms for optimal transport", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3230. Accessed: Jun. 20, 2018.
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. (2018). Multi-scale algorithms for optimal transport. IEEE SigPort. http://sigport.org/3230
, 2018. Multi-scale algorithms for optimal transport. Available at: http://sigport.org/3230.
. (2018). "Multi-scale algorithms for optimal transport." Web.
1. . Multi-scale algorithms for optimal transport [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3230