SE-QRCS selects k representative columns of a wide matrix by applying strong rank-revealing QR to a sparse sketch and to the small induced column set, with spectral bounds that shrink the dependence on n.
Communication avoiding low rank approximation based on qr with tournament pivoting
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Efficient QR-based Column Subset Selection through Randomized Sparse Embeddings
SE-QRCS selects k representative columns of a wide matrix by applying strong rank-revealing QR to a sparse sketch and to the small induced column set, with spectral bounds that shrink the dependence on n.