Talk
Affine Natural Proximal Learning
- Alex Tong Lin (MPI MiS, Leipzig + Department of Mathematics, UCLA)
Abstract
We revisit the natural gradient method for learning. Here we consider the proximal formulation and obtain a closed-form approximation of the proximal term over an affine subspace of functions. We mainly consider the two statistical metrics: the Wasserstein metric, and the Fisher-Rao metric, and we introduce numerical methods for high-dimensional parameter spaces.
