Geometric Methods of Machine Learning (II): Nonlinear Methods
组织者
演讲者
时间
2023年10月13日 20:00 至 20:30
地点
Online
摘要
We pick up where we left off in the last presentation and continue to summarize the book Mathematical Principles of Topological and Geometric Data Analysis. In recent years, we have seen the fascinating development that concepts and methods developed in the context of research in pure mathematics, and in particular in geometry, have become powerful tools in machine learning for the analysis of data. In this book, we shall first develop the background from topology, geometry, measure theory, graph theory in Chaps. 2-5 and then systematically present and analyze geometric methods of machine learning in Chaps. 6, 7 and 8. This presentation is about Chap 7, which discusses nonlinear methods, including clustering, feature extraction and dimension reduction.