Subspace Iteration Randomization and Singular Value Problems
Subspace Iteration Randomization and Singular Value Problems
A classical problem in matrix computations is the efficient and reliable approximation of a given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is known to provide the best such approximation for any given fixed rank. However, the SVD is also known to be very …