SLRA: Structured Low-Rank Approximation as Optimization on a Grassmann Manifold - implementation -

From this presentation on Structured Low-Rank Approximation as Optimization on a Grassmann Manifold by Konstantin Usevich, here is SLRA a structured low-rank approximation algorithm using an optimization on a Grassmann manifold. The Matlab/Octave/R code is on GitHub at: https://github.com/slra/slra/

Structured Low-Rank Approximation as Optimization on a Grassmann Manifold
Konstantin Usevich

Attendant relevant papers include:

• Variable projection methods for affinely structured low-rank approximation in weighted 2-norms
• Variable projection methods for approximate (greatest) common divisor computations
• Global and local optimization methods for structured low-rank approximation
• “Optimization on the Grassmann manifold: a case study” (slides)
• “Fast algorithms and software for weighted mosaic-Hankel-like low-rank approximation” (slides)

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