Neighborhood Preserving Nonnegative Matrix Factorization

  title={Neighborhood Preserving Nonnegative Matrix Factorization},
  author={Quanquan Gu and Jie Zhou},
Nonnegative Matrix Factorization (NMF) [2] has been widely used in computer vision and pattern recognition. It aims to find two nonnegative matrices whose product can well approximate the nonnegative data matrix, which naturally leads to parts-based and non-subtractive representation. Recent years, many variants of NMF have been proposed. [3] proposed a local NMF (LNMF) which imposes a spatially localized constraint on the bases. All the methods mentioned above are unsupervised, while [5… CONTINUE READING
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Convex optimization

  • Stephen Boyd, Lieven Vandenberghe
  • 2004
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