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Higham, N.J. (1989) Matrix Nearness Problems and Applications. In: Gover, M.J.C. and Barnett, S., Eds., Applications of Matrix Theory, Oxford University Press, Oxford, 1-27.

has been cited by the following article:

• TITLE: Low-Rank Positive Approximants of Symmetric Matrices

  AUTHORS: Achiya Dax

  KEYWORDS: Low-Rank Positive Approximants, Unitarily Invariant Matrix Norms

  JOURNAL NAME: Advances in Linear Algebra & Matrix Theory, Vol.4 No.3, September 25, 2014

  ABSTRACT: Given a symmetric matrix X, we consider the problem of finding a low-rank positive approximant of X. That is, a symmetric positive semidefinite matrix, S, whose rank is smaller than a given positive integer, , which is nearest to X in a certain matrix norm. The problem is first solved with regard to four common norms: The Frobenius norm, the Schatten p-norm, the trace norm, and the spectral norm. Then the solution is extended to any unitarily invariant matrix norm. The proof is based on a subtle combination of Ky Fan dominance theorem, a modified pinching principle, and Mirsky minimum-norm theorem.