RandSVD

Build Status Gem Version

RandSVD is a class that performs truncated singular value decomposition using a randomized algorithm. To implement, I referred to the following papers:

  • P.-G. Martinsson, A. Szlam, M. Tygert, "Normalized power iterations for the computation of SVD," Proc. of NIPS Workshop on Low-Rank Methods for Large-Scale Machine Learning, 2011.
  • P.-G. Martinsson, V. Rokhlin, M. Tygert, "A randomized algorithm for the approximation of matrices," Tech. Rep., 1361, Yale University Department of Computer Science, 2006.

Installation

Add this line to your application's Gemfile:

gem 'randsvd'

And then execute:

$ bundle

Or install it yourself as:

$ gem install randsvd

Usage

require 'randsvd'

# Initialize some variables.
input_matrix = NMatrix.rand([1000, 100])
nb_singular_values = 10

# Perform the randomized singular value decomposition.
u, s, vt = RandSVD.gesvd(input_matrix, nb_singular_values)

# Reconstruct the matrix with the singular values and vectors.
reconstructed_matrix = u.dot(NMatrix.diag(s).dot(vt))

Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/yoshoku/randsvd. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

License

The gem is available as open source under the terms of the MIT License.