Unsupervised dimensionality reduction: the challenge of big data visulisation
Kerstin Bunte, John A. Lee · The European Symposium on Artificial Neural Networks · 2015
Dimensionality reduction is an unsupervised task that allows high-dimensional data to be processed or visualised in lower-dimensional spaces. This tutorial reviews the basic principles of dimensionality reduc- tion and discusses some of the approaches that were published over the past years from the perspective of their application to big data. The tu- torial ends with a short review of papers about dimensionality reduction in these proceedings, as well as some perspectives for the near future.