Accueil Explorer Aide
Connexion
puigt
/
Faster-than-fast_NMF
1
0
Fork 0
Fichiers Tickets 0 Pull Requests 0 Wiki

Matlab code for Non-negative Matrix Factorization combining random projections and Nesterov iterations

Aborescence: 1d07b98803
Branches Tags
Faster-than-...
ZIP TAR.GZ
Matthieu PUIGT 1d07b98803 Supprimer 'add_paths.m' il y a 5 ans
Code ee2c9669a7 Transférer les fichiers vers 'Code/algorithms' il y a 5 ans
README.md 0c3b9e6c34 Mettre à jour 'README.md' il y a 5 ans
plots.m 0cf0905a24 Transférer les fichiers vers '' il y a 5 ans
stop_rule.m 0cf0905a24 Transférer les fichiers vers '' il y a 5 ans

README.md

Faster-than-fast NMF using random projections and Nesterov iterations

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 that structured random projections significantly speed-up NeNMF for very large data matrices.

Purpose

ToWrite

Download

Reference

F. Yahaya, M. Puigt, G. Delmaire, and G. Roussel, "Faster-than-fast NMF using random projections and Nesterov iterations," in Proc. of iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Marseille, France, November 21-23, 2018.