iSVD

Integrated Singular Value Decomposition

iSVD is a parallel low-rank approximate singular value decomposition solver using integrated randomized algorithm.

Videos

External Links

GitHub
Documentation
“Integrating Multiple Random Sketches for Singular Value Decomposition”
Ting-Li Chen, Dawei D. Chang, Su-Yun Huang, Hung Chen, Chienyao Lin, Weichung Wang
arXiv preprint arXiv:1608.08285, 2016
“Theoretical and Performance Analysis for Integrated Randomized Singular Value Decomposition”
Dawei D. Chang
Master’s thesis, National Taiwan University, 2017
“Highly Scalable Parallelism of Integrated Randomized Singular Value Decomposition with Big Data Applications”
Mu Yang
Master’s thesis, National Taiwan University, 2017
MCNLA

Contributors

  • Ting-Li Chen
  • Dawei D. Chang
  • Hung Chen
  • Su-Yun Huang
  • Chen-Yao Lin
  • Weichung Wang
  • Mu Yang