Stochastic Proximity Embedding on Graphics Processing Units: Taking Multidimensional Scaling to a New Scale

Abstract

Stochastic proximity embedding (SPE) was developed as a method for efficiently calculating lower dimensional embeddings of high-dimensional data sets. Rather than using a global minimization scheme, SPE relies upon updating the distances of randomly selected points in an iterative fashion. This was found to generate embeddings of comparable quality to those… (More)
DOI: 10.1021/ci200420c

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