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Improved Low-rank Matrix Decompositions via the Subsampled Randomized Hadamard Transform

We comment on two randomized algorithms for constructing low-rank matrix decompositions. Both algorithms employ the Subsampled Randomized Hadamard Transform. We provide a novel analysis that significantly improves previous approximation bounds.

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approximation error bounds for low rank approximation of matrices using subsampled randomized hadamard transforms

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