Wasserstein Distance to Independence Models

Abstract: An independence model for discrete random variables is a variety in a probability simplex. Given any data distribution, we seek to minimize the Wasserstein distance to the model. That distance comes from a polyhedral norm whose unit ball is dual to an alcoved polytope. The solution to our optimization problem is a piecewise algebraic function of the data. In this talk we discuss the algebraic and geometric structure of this function.

Reference: arXiv:2003.06725

algebraic geometryoptimization and control

Audience: learners

Comments: The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk

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One World Optimization seminar

Series comments: Description: Online seminar on optimization and related areas

The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk

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