Corpus ID: 17934800

Nonnegative Matrix Approximation: Algorithms and Applications

@inproceedings{Sra2006NonnegativeMA,
  title={Nonnegative Matrix Approximation: Algorithms and Applications},
  author={S. Sra},
  year={2006}
}
  • S. Sra
  • Published 2006
  • Mathematics
Low dimensional data representations are crucial to numerous applicatio ns in machine learning, statistics, and signal processing. Nonnegative matrix approximation (NNMA) is a method for dimensionality reduction that respects the nonnegativity of the input data while constructin g a low-dimensional approximation. NNMA has been used in a multitude of applications, though without com mensurate theoretical development. In this report we describe generic methods for minimizing g e eralized… Expand

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