Least Squares Approximation Task

A Least Squares Approximation Task is a least-squares task that is an approximation task.

• See: Exact Last-Squares, Low-Rank Matrix Approximation.

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References

2011

• (Mahoney, 2011) ⇒ Michael W. Mahoney. (2011). “Randomized Algorithms for Matrices and Data.” Now Publishers Inc.. ISBN:1601985061, 9781601985064
  • QUOTE: Randomized Algorithms for Matrices and Data provides a detailed overview, appropriate for both students and researchers from all of these areas, of recent work on the theory of randomized matrix algorithms as well as the application of those ideas to the solution of practical problems in large-scale data analysis. By focusing on ubiquitous and fundamental problems such as least squares approximation and low-rank matrix approximation that have been at the center of recent developments, an emphasis is placed on a few simple core ideas that underlie not only recent theoretical advances but also the usefulness of these algorithmic tools in large-scale data applications.

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