Geert-Jan Huizing

Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors

Defining meaningful distances between samples in a dataset is a fundamental problem in machine learning. Optimal Transport (OT) lifts a distance between features (the "ground metric") to a geometrically meaningful distance between samples. However, there is usually no straightforward choice of groun…