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FAµST python toolbox

Project description

The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation). FaµST can be used to:

  • speedup / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems,

  • learn dictionaries with an intrinsically efficient implementation,

  • compute (approximate) fast Fourier transforms on graphs.

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