Faster-than-fast NMF using random projections and Nesterov iterations
Signal Processing
2018-12-12 v1 Information Theory
math.IT
Abstract
Random projections have been recently implemented in Nonnegative Matrix Factorization (NMF) to speed-up the NMF computations, with a negligible loss of performance. In this paper, we investigate the effects of such projections when the NMF technique uses the fast Nesterov gradient descent (NeNMF). We experimentally show the randomized subspace iteration to significantly speed-up NeNMF.
Cite
@article{arxiv.1812.04315,
title = {Faster-than-fast NMF using random projections and Nesterov iterations},
author = {Farouk Yahaya and Matthieu Puigt and Gilles Delmaire and Gilles Roussel},
journal= {arXiv preprint arXiv:1812.04315},
year = {2018}
}
Comments
in Proceedings of iTWIST'18, Paper-ID: 28, Marseille, France, November, 21-23, 2018