Yakov Gavriyelov

RECOVERING WASSERSTEIN DISTANCE MATRICES FROM FEW MEASUREMENTS

This paper proposes two algorithms for estimating square Wasserstein distance matrices from a small number of entries. These matrices are used to compute manifold learning embeddings like multidimensional scaling (MDS) or Isomap, but contrary to Euclidean distance matrices, are extremely costly to c…