Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
Abstract—Non-negative matrix factorization (NMF) has recently received a lot of attention in data mining, information retrieval, and computer vision. It factorizes a non-negative...
Christian Thurau, Kristian Kersting, Christian Bau...
There is an exploding amount of user-generated content on the Web due to the emergence of "Web 2.0" services, such as Blogger, MySpace, Flickr, and del.icio.us. The part...
Ka Cheung Sia, Junghoo Cho, Yun Chi, Belle L. Tsen...
— Non-negative Matrix factorization (NMF) has increasingly been used as a tool in signal processing in the last couple of years. NMF, like independent component analysis (ICA) is...
Matrix factorization methods are among the most common techniques for detecting latent components in data. Popular examples include the Singular Value Decomposition or Nonnegative...
Christian Thurau, Kristian Kersting, Christian Bau...