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Non-negative matrix factorization

Known as: Approximate nonnegative matrix factorization, NMF, Nonnegative matrix decomposition 
Non-negative matrix factorization (NMF), also non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra… Expand
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Review
2018
Review
2018
Abstract The modern science of networks has made significant advancement in the modeling of complex real-world systems. One of… Expand
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Highly Cited
2010
Highly Cited
2010
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine… Expand
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Highly Cited
2009
Highly Cited
2009
We present a Bayesian treatment of non-negative matrix factorization (NMF), based on a normal likelihood and exponential priors… Expand
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Highly Cited
2008
Highly Cited
2008
Recently non-negative matrix factorization (NMF) has received a lot of attentions in information retrieval, computer vision and… Expand
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Highly Cited
2004
Highly Cited
2004
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non… Expand
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Highly Cited
2004
Highly Cited
2004
In this paper we explore a recent iterative compression technique called non-negative matrix factorization (NMF). Several special… Expand
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Highly Cited
2003
Highly Cited
2003
In this paper, we propose a novel document clustering method based on the non-negative factorization of the term-document matrix… Expand
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Highly Cited
2003
Highly Cited
2003
We present a methodology for analyzing polyphonic musical passages comprised of notes that exhibit a harmonically fixed spectral… Expand
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Highly Cited
2002
Highly Cited
2002
  • P. O. Hoyer
  • Proceedings of the 12th IEEE Workshop on Neural…
  • 2002
  • Corpus ID: 6386670
Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. We briefly describe… Expand
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Highly Cited
2000
Highly Cited
2000
Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two… Expand
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