Exact multiplicative updates for convolutional $\beta$-NMF in 2D
Machine Learning
2024-09-13 v1 Data Structures and Algorithms
Machine Learning
Abstract
In this paper, we extend the -CNMF to two dimensions and derive exact multiplicative updates for its factors. The new updates generalize and correct the nonnegative matrix factor deconvolution previously proposed by Schmidt and M{\o}rup. We show by simulation that the updates lead to a monotonically decreasing -divergence in terms of the mean and the standard deviation and that the corresponding convergence curves are consistent across the most common values for .
Cite
@article{arxiv.1811.01661,
title = {Exact multiplicative updates for convolutional $\beta$-NMF in 2D},
author = {Pedro J. Villasana T. and Stanislaw Gorlow},
journal= {arXiv preprint arXiv:1811.01661},
year = {2024}
}