Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), pp. 2537-2548, 2019.
We study the low rank approximation problem of any given matrix A over l """ and C'm in entry -wise fp loss, that is, finding a rank -1 matrix X such that is minimized Unlike the traditional,e2 setting, this particular variant is NP -Hard. We show that the algorithm of column subset selection, which was an algorithmic foundation of many e...More
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