Lifting functionals defined on maps to measure-valued maps via optimal transport
How can one lift a functional defined on maps from a space X to a space Y into a functional defined on maps from X into P(Y) the space of probability distributions over Y? Looking at measure-valued maps can be interpreted as knowing a classical map with uncertainty, and from an optimization point of...
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Main Author | |
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Format | Journal Article |
Language | English |
Published |
05.09.2023
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Subjects | |
Online Access | Get full text |
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Summary: | How can one lift a functional defined on maps from a space X to a space Y
into a functional defined on maps from X into P(Y) the space of probability
distributions over Y? Looking at measure-valued maps can be interpreted as
knowing a classical map with uncertainty, and from an optimization point of
view the main gain is the convexification of Y into P(Y). We will explain why
trying to single out the largest convex lifting amounts to solve an optimal
transport problem with an infinity of marginals which can be interesting by
itself. Moreover we will show that, to recover previously proposed liftings for
functionals depending on the Jacobian of the map, one needs to add a
restriction of additivity to the lifted functional. |
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DOI: | 10.48550/arxiv.2309.02260 |