Stochastic Neighbor Embedding

Abstract

We describe a probabilistic approach to the task of embedding highdimensional objects into a low-dimensional space in a way that preserves neighbor identities. A Gaussian is centered on each object in the highdimensional space and the densities under this Gaussian are used to define a probability distribution over all the potential neighbors of the object.