Skip to content

ImKeTT/Low-rank_Matrix-completion

Repository files navigation

Low Rank Matrix Completion

Introduction

Implementations of algorithms in this repository will focus on completing low rank matrixes . Including traditional matrix trace and nuclear norm minimization as well as some algorithms related to the popular differentiable programming. They are all implemented in python or MATLAB.

Algorithms

  1. SVT (A Singular Value Thresholding Algorithm for Matrix Completion)
  2. Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization(find the paper here)
  3. Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery
  4. ...

Dataset

  • ml-1M from MovieLens
  • ml-100k from MovieLens
  • Netflix Dataset from Netflix

More to be continued...

About

[Tool] Low rank matrix recovery by minimizing matrix norm

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published