Convex non-negative matrix factorization for massive datasets

Abstract

Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix into two non-negative matrix factors that contain basis elements and linear coefficients, respectively. Often, the columns of the first resulting factor are interpreted as… (More)
DOI: 10.1007/s10115-010-0352-6

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