Geometry and Statistics: Manifolds and Stratified Spaces

Statistics and machine learning typically take place in linear spaces. When data points are described by fixed-dimensional vector measurements, analysis takes place in a Euclidean space, and when data is analyzed using kernels, analysis takes place in a reproducing kernel Hilbert space. Geometry enters statistics and machine learning when explicit models… (More)