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csalgs: Compressed sensing algorithms in Python

This is a small collection of compressed sensing/low rank matrix recovery algorithms in Python. It's neither complete nor very elaborate -- it's mainly just for learning exisiting algorithms or for testing purposes. Use at your own risk :)

Content

  • csalg.tt: Low-rank tensor recovery for the tensor train format
    • iht.py: Iterative hard thresholding (projected gradient descent)
    • altmin.py: Alternating Least Squares
    • _altmin_gpu.py: A CUDA implementation of alternating least squares
  • csalgs.lowrank: Low-rank matrix recovery
    • gradient.py: Gradient based schemes such as Iterative hard thresholding (projected gradient descent) and conjugated gradient descent
    • convex.py: Convex optimization methods (nuclear norm minimization and constrained l2 minimization)
    • altmin.py: Alternating Least Squares
  • csalg.cs: Compressed Sensing (Recovery of sparse vectors)
    • iht.py: Iterative hard thresholding (projected gradient descent)

LICENSE

Distributed under the terms of the GPLv3 license (see LICENSE).