GeometryOfData

Modern data are high-dimensional, for example, images with millions of pixels, text corpora with millions of words, gene sequences with billions of base pairs, etc. However, these data tend to concentrate on lower-dimensional, nonlinear subspaces known as manifolds. This covers the mathematical theory of high-dimensional geometry and manifolds and the application of this geometry to machine learning and data analysis.