Volume-based Subset Selection
NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS(2024)
摘要
This paper provides a fast algorithm for the search of a dominant (locally maximum volume) submatrix, generalizing the existing algorithms from n ? r to n > r submatrix columns, where r is the number of searched rows. We prove the bound on the number of steps of the algorithm, which allows it to outper-form the existing subset selection algorithms in either the bounds on the norm of the pseudoinverse of the found submatrix, or the bounds on the complexity, or both.
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关键词
locally maximum volume,optimal design,sparse approximation,subset selection
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