BIMSA > Seminar on Control Theory and Nonlinear Filtering Geometric Methods of Machine Learning (III): UMAP
Geometric Methods of Machine Learning (III): UMAP
Organizer
Shing Toung Yau
Speaker
Minli Feng
Time
Friday, November 3, 2023 8:30 PM - 9:00 PM
Venue
Online
Abstract
UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that is applicable to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP has no computational restrictions on embedding dimension, making it viable as a general purpose dimension reduction technique for machine learning.