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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

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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