Kantorovich Dual Problem (for general costs): Difference between revisions

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==Statement of Theorem==
==Statement of Theorem==


'''Theorem.''(Kantorovich Duality) Let X and Y be Polish spaces, let <math>\mu \in \mathcal{P}(X)</math> and <math>\nu \in \mathcal{P}(Y)</math>, and let a cost function <math> c:X \times Y \rightarrow[0,+\infty] </math> be lower semi-continuous.
: '''Theorem.'''<ref name=Villani /> Let X and Y be Polish spaces, let <math>\mu \in \mathcal{P}(X)</math> and <math>\nu \in \mathcal{P}(Y)</math>, and let a cost function <math> c:X \times Y \rightarrow[0,+\infty] </math> be lower semi-continuous.
Whenever <math> \pi \in \mathcal{P}(X \times Y) </math> and <math> (\varphi, \psi) \in L^{1}(d\mu) \times L^{1}(d\nu) </math>, define <br>
Whenever <math> \pi \in \mathcal{P}(X \times Y) </math> and <math> (\varphi, \psi) \in L^{1}(d\mu) \times L^{1}(d\nu) </math>, define <br>



Revision as of 23:21, 16 May 2020

Introduction

The main advantage of Kantorovich Problem, in comparison to Monge problem, is in the convex constraint property. It is possible to formulate the dual problem.

Statement of Theorem

Theorem.[1] Let X and Y be Polish spaces, let and , and let a cost function be lower semi-continuous.

Whenever and , define

.

Define to be the set of Borel probability measures on such that for all measurable sets and ,

, ,

and define to be the set of all measurable functions satisfying for almost everywhere in X and almost everywhere in Y.

Then .

Moreover, the infimum is attained. In addition it is possible to restrict and to be continuous and bounded.

Proof of Theorem

References

  1. Cite error: Invalid <ref> tag; no text was provided for refs named Villani

[1]

[2]

</ references>

  1. C. Villani, Topics in Optimal Transportation, Chapter 1. (pages 17-21)
  2. https://link-springer-com.proxy.library.ucsb.edu:9443/book/10.1007/978-3-319-20828-2 F. Santambrogio, Optimal Transport for Applied Mathematicians, Chapter 1.] (pages 9-16)