SVD based initialization: A head start for nonnegative matrix factorization Export

@misc{citeulike:3106860, abstract = {We describe Nonnegative Double Singular Value Decomposition (NNDSVD), a new method designed to enhance the initialization stage of nonnegative matrix factorization (NMF). NNDSVD can readily be combined with existing NMF algorithms. The basic algorithm contains no randomization and is based on approximations of positive sections of the partial SVD factors of the data matrix utilizing an algebraic property of unit rank matrices. Simple practical variants for NMF with dense factors are described. NNDSVD is also well suited to initialize NMF algorithms with sparse factors. Many numerical examples suggest that NNDSVD leads to rapid reduction of the approximation error of many NMF algorithms.}, author = {Factorization, Matrix and Boutsidis, C. and Gallopoulos, E. and Boutsidis and Gallopoulos}, citeulike-article-id = {3106860}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.2579}, keywords = {nmf}, posted-at = {2009-01-06 13:37:52}, priority = {0}, title = {SVD based initialization: A head start for nonnegative matrix factorization}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.2579}, year = {2007} }

TY - ELEC ID - citeulike:3106860 L3 - citeulike-article-id:3106860 N2 - We describe Nonnegative Double Singular Value Decomposition (NNDSVD), a new method designed to enhance the initialization stage of nonnegative matrix factorization (NMF). NNDSVD can readily be combined with existing NMF algorithms. The basic algorithm contains no randomization and is based on approximations of positive sections of the partial SVD factors of the data matrix utilizing an algebraic property of unit rank matrices. Simple practical variants for NMF with dense factors are described. NNDSVD is also well suited to initialize NMF algorithms with sparse factors. Many numerical examples suggest that NNDSVD leads to rapid reduction of the approximation error of many NMF algorithms. TI - SVD based initialization: A head start for nonnegative matrix factorization KW - nmf AU - Factorization, Matrix AU - Boutsidis, C AU - Gallopoulos, E AU - Boutsidis AU - Gallopoulos PY - 2007/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.2579 ER -