Computing Wasserstein barycenters using gradient descent algorithms
[Moved Online] Hot Topics: Optimal transport and applications to machine learning and statistics May 04, 2020 - May 08, 2020
Location: SLMath: Online/Virtual
Tags/Keywords
Barycenters
gradient descent
optimal transport
Bures manifold
Polyak-Lojasiewicz inequality
Computing Wasserstein Barycenters Using Gradient Descent Algorithms
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.
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Computing Wasserstein Barycenters Using Gradient Descent Algorithms
H.264 Video | 928_28410_8313_Computing_Wasserstein_Barycenters_Using_Gradient_Descent_Algorithms.mp4 |
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