Date Thesis Awarded
4-2020
Access Type
Honors Thesis -- Access Restricted On-Campus Only
Degree Name
Bachelors of Science (BS)
Department
Mathematics
Advisor
Charles Johnson
Committee Members
Gexin Yu
Martin White
Abstract
The Nonnegative Matrix Factorization (NMF) problem has been widely used to analyze high-dimensional nonnegative data and extract important features. In this paper, I review major concepts regarding NMF, some NMF algorithms and related problems including initialization strategies and near separable NMF. Finally I will implement algorithms on generated and real data to compare their performances.
Recommended Citation
An, Junda, "Nonnegative Matrix Factorization Problem" (2020). Undergraduate Honors Theses. William & Mary. Paper 1518.
https://scholarworks.wm.edu/honorstheses/1518
