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Simple and practical algorithms for $ell_p$-norm low-rank approximation

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 نشر من قبل Anastasios Kyrillidis
 تاريخ النشر 2018
  مجال البحث الهندسة المعلوماتية
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We propose practical algorithms for entrywise $ell_p$-norm low-rank approximation, for $p = 1$ or $p = infty$. The proposed framework, which is non-convex and gradient-based, is easy to implement and typically attains better approximations, faster, than state of the art. From a theoretical standpoint, we show that the proposed scheme can attain $(1 + varepsilon)$-OPT approximations. Our algorithms are not hyperparameter-free: they achieve the desiderata only assuming algorithms hyperparameters are known a priori---or are at least approximable. I.e., our theory indicates what problem quantities need to be known, in order to get a good solution within polynomial time, and does not contradict to recent inapproximabilty results, as in [46].



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