About Nonnegative Matrix Factorization: on the posrank approximation



This work addresses the concept of nonnegative matrix factorization (NMF). Some relevant issues for its formulation as as a nonlinear optimization problem will be discussed. The primary goal of NMF
is that of obtaining good quality approximations, namely for video/image visualization. The importance of the rank of the factor matrices and
the use of global optimization techniques is investigated. Some computational experience is reported indicating that, in general, the relation
between the quality of the obtained local minima and the factor matrices dimensions has a strong impact on the quality of the solutions associated
with the decomposition.


Signal processing, non negative matrix factorization, feature extraction, dimensionality reduction


Feature Extraction and Combinatorial Optimization


Proc Intl Conf on Adaptive and Natural Computing Algorithms, Part II, LNCS 6594, 2011, April 2011

Cited by

Year 2012 : 1 citations

 Tadeusz KACZOREK, "FACTORIZATION OF NONNEGATIVE MATRICES BY THE USE OF ELEMENTARY OPERATION", acta mechanica et automatica, vol.6 no.4, 15-18, 2012

Year 2011 : 1 citations

 “The optimal approximation solution associated with a nonnegative definite constraint matrix
equation”, Dong-Xiu Xie Juan Zeng, Proc. of the International Conference on Machine
Learning and Cybernetics (ICMLC), 2011.