—This study examines the ability of nonnegative matrix factorization (NMF) as a method for constructing semantic spaces, in which the meaning of each word is represented by a hig...
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
Abstract--We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of sourc...
Nonnegative Matrix Factorization (NMF) is a dimension reduction method that has been widely used for various tasks including text mining, pattern analysis, clustering, and cancer ...
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...