Algorithms for `p Low-Rank Approximation
نویسندگان
چکیده
We consider the problem of approximating a given matrix by a low-rank matrix so as to minimize the entry-wise `p-approximation error, for any p ≥ 1; the case p = 2 is the classical SVD problem. We obtain the first provably good approximation algorithms for this version of lowrank approximation that work for every value of p ≥ 1, including p =∞. Our algorithms are simple, easy to implement, work well in practice, and illustrate interesting tradeoffs between the approximation quality, the running time, and the rank of the approximating matrix.
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