Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4602221 | Linear Algebra and its Applications | 2008 | 6 Pages |
Abstract
In this short note, we focus on the use of the generalized Kullback–Leibler (KL) divergence in the problem of non-negative matrix factorization (NMF). We will show that when using the generalized KL divergence as cost function for NMF, the row sums and the column sums of the original matrix are preserved in the approximation. We will use this special characteristic in several approximation problems.
Related Topics
Physical Sciences and Engineering
Mathematics
Algebra and Number Theory