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Low-rank Approximations for Large Incomplete Matrices. Project for NLA and Optimization Methods courses at Skoltech

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Low-rank Approximations for Large Incomplete Matrices

This is a project for Numerical Linear Algebra and Optimization Methods courses at Skoltech, 2017.

Team memebers:

  • Liliya Ageeva
  • Sergey Makarychev
  • Aleksandr Rozhnov
  • Anton Zhevnerchuk

There are three modules, each of them containes a documented implementation of one of the matrix-completion algorithms. Jupyter Notebook with the demonstration of their performances is represented as well. For more detailes see presentation and report.

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Low-rank Approximations for Large Incomplete Matrices. Project for NLA and Optimization Methods courses at Skoltech

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