Corpus ID: 15852417

An implementation of a randomized algorithm for principal component analysis

@article{Szlam2014AnIO,
  title={An implementation of a randomized algorithm for principal component analysis},
  author={Arthur Szlam and Yuval Kluger and Mark Tygert},
  journal={ArXiv},
  year={2014},
  volume={abs/1412.3510}
}
  • Arthur Szlam, Yuval Kluger, Mark Tygert
  • Published in ArXiv 2014
  • Mathematics, Computer Science
  • Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis (PCA) and the calculation of truncated singular value decompositions (SVD). The present paper presents an essentially black-box, fool-proof implementation for Mathworks' MATLAB, a popular software platform for numerical computation. As illustrated via several tests, the randomized algorithms for low-rank approximation outperform or at least match… CONTINUE READING

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