Banff International Research Station for Mathematical Innovation and Discovery
Abstract
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has shown its effectiveness in discerning true features from noise in high-dimensional data. In this talk, we will introduce persistent homology, a particular branch of computational topology and discuss how it can be incorporated to classical statistics and techniques in machine learning. We will demonstrate its usefulness in classifying ADHD subjects.
This is a joint project with Rui Hu, Zhichun Zhai, Linglong Kong and Bei Jiang.Non UBCUnreviewedAuthor affiliation: University of AlbertaFacult
