Converged Algorithms for Orthogonal Nonnegative Matrix Factorizations
Machine Learning
2011-03-17 v2 Numerical Analysis
Abstract
This paper proposes uni-orthogonal and bi-orthogonal nonnegative matrix factorization algorithms with robust convergence proofs. We design the algorithms based on the work of Lee and Seung [1], and derive the converged versions by utilizing ideas from the work of Lin [2]. The experimental results confirm the theoretical guarantees of the convergences.
Cite
@article{arxiv.1010.5290,
title = {Converged Algorithms for Orthogonal Nonnegative Matrix Factorizations},
author = {Andri Mirzal},
journal= {arXiv preprint arXiv:1010.5290},
year = {2011}
}
Comments
55 pages, 11 figures