DocumentCode :
3731740
Title :
Global convergence of a modified HALS algorithm for nonnegative matrix factorization
Author :
Takumi Kimura;Norikazu Takahashi
Author_Institution :
Okayama University, 700-8530 Japan
fYear :
2015
Firstpage :
21
Lastpage :
24
Abstract :
Hierarchical alternating least squares (HALS) algorithms are efficient computational methods for nonnegative matrix factorization (NMF). Given an initial solution, HALS algorithms update the solution block by block iteratively so that the error decreases monotonically. However, update rules in HALS algorithms are not well-defined. In addition, due to this problem, the convergence of the sequence of solutions to a stationary point cannot be proved theoretically. In this paper, we consider the HALS algorithm for the Frobenius norm-based NMF, and prove that a modified version has the global convergence property in the sense of Zangwill.
Keywords :
"Convergence","Optimization","Approximation algorithms","Conferences","Manganese","Linear programming","Partitioning algorithms"
Publisher :
ieee
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015 IEEE 6th International Workshop on
Type :
conf
DOI :
10.1109/CAMSAP.2015.7383726
Filename :
7383726
Link To Document :
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