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Entropy-Regularized $2$-Wasserstein Distance between Gaussian Measures
As the geometries change by varying the regularization magnitude, we study the limiting cases of vanishing and infinite magnitudes, reconfirming well-known results on the limits of the Sinkhorn divergence.
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification
This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input features in the paradigm of kernel methods on infinite-dimensional Riemannian manifolds.
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