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Column Subset Selection, Matrix Factorization, and Eigenvalue Optimization
[chapter]

2009
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Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
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Given a fixed matrix, the problem of column subset selection requests a column submatrix that has favorable spectral properties. Most research from the algorithms and numerical linear algebra communities focuses on a variant called rank-revealing QR, which seeks a well-conditioned collection of columns that spans the (numerical) range of the matrix. The functional analysis literature contains another strand of work on column selection whose algorithmic implications have not been explored. In

doi:10.1137/1.9781611973068.106
fatcat:2575gcq7nzfehpwmyxmq6qtrvy