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Top 6 singular values and vectors of sparse matrices by svt, svds and svd. Reported are the average run time (in seconds) and standard error (in parentheses) based on 10 runs.

Journal: Journal of statistical software

Article Title: svt: Singular Value Thresholding in MATLAB

doi: 10.18637/jss.v081.c02

Figure Lengend Snippet: Top 6 singular values and vectors of sparse matrices by svt, svds and svd. Reported are the average run time (in seconds) and standard error (in parentheses) based on 10 runs.

Article Snippet: When a fixed number of top singular values and vectors are requested, svt expands the capability of MATLAB’s built-in function svds by allowing function handle input.

Techniques:

Top 6 singular values and vectors of “sparse + low rank” matrices by svt and svds. Structured matrices are formed by adding a random rank-10 matrix to the original sparse test matrix. Reported are the average run time (in seconds) and standard error (in parentheses) based on 10 simulation replicates.

Journal: Journal of statistical software

Article Title: svt: Singular Value Thresholding in MATLAB

doi: 10.18637/jss.v081.c02

Figure Lengend Snippet: Top 6 singular values and vectors of “sparse + low rank” matrices by svt and svds. Structured matrices are formed by adding a random rank-10 matrix to the original sparse test matrix. Reported are the average run time (in seconds) and standard error (in parentheses) based on 10 simulation replicates.

Article Snippet: When a fixed number of top singular values and vectors are requested, svt expands the capability of MATLAB’s built-in function svds by allowing function handle input.

Techniques: