Approximating Matrix p-norms

  title={Approximating Matrix p-norms},
  author={Aditya Bhaskara and Aravindan Vijayaraghavan},
We consider the problem of computing the <i>q</i> ↦ <i>p</i> norm of a matrix <i>A</i>, which is defined for <i>p, q</i> ≥ 1, as [EQUATION] This is in general a non-convex optimization problem, and is a natural generalization of the well-studied question of computing singular values (this corresponds to <i>p</i> = <i>q</i> = 2). Different settings of parameters give rise to a variety of known interesting problems (such as the Grothendieck problem when <i>p</i> = 1 and <i>q</i> = ∞). However… CONTINUE READING
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