Talk page

Title:
Computing Wasserstein barycenters using gradient descent algorithms

Speaker:
Philippe Rigollet

Abstract:
In this talk, I will present rates of convergence for Wasserstein barycenters using gradient descent and stochastic gradient descent. While the barycenter functional is not geodesically convex, this result hinges on a Polyak-Lojasiewicz (PL) inequality in the case where the underlying distribution is supported on a subset of Gaussian distributions.

Link:
https://www.msri.org/workshops/928/schedules/28410

Workshop:
MSRI- [Moved Online] Hot Topics: Optimal transport and applications to machine learning and statistics