Avner Magen

  1. Low Rank Matrix-Valued Chernoff Bounds and Applications.

    Authors: Anastasios Zouzias, Avner Magen
    Subjects: Data Structures and Algorithms
    Abstract

    In this paper we develop algorithms for approximating matrix multiplication
    with respect to the spectral norm. Let A\in{\RR^{n\times m}} and B\in{\RR^{n
    \times p}} be two matrices and \eps>0. We approximate the product A^\top B
    using two down-sampled sketches, \tilde{A}\in{\RR^{t\times m}} and
    \tilde{B}\in{\RR^{t\times p}}, such that \norm{\tilde{A}^\top \tilde{B} -
    A^\top B} \leq \eps \norm{A}\norm{B} with constant probability. We use two
    different sampling procedures for constructing \tilde{A} and \tilde{B}; one of
    them is done by i.i.d.

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