User talk:Wotao.yin

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Revision as of 03:57, 5 November 2010 by Dattorro (Talk | contribs)
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I regard the following as a difficult problem, having spent considerable time with it.

LaTeX: \begin{array}{cl}\mbox{minimize}_X&c^{\rm T}\mbox{vec}\,X\\ \mbox{subject to}&A\,\mbox{vec}\,X=b\\ &X^{\rm T\!}X=I\\ &X\geq_{}\mathbf{0}\end{array}

Vector LaTeX: c\, is left unspecified beause I may want to vary it later in a convex iteration. For your purposes, it may arbitrarily be set to LaTeX: \mathbf{0} or LaTeX: \mathbf{1}.

Rectangular submatrix LaTeX: \,X\!\in\mathbb{R}^{1024\times256}\, comes from a permutation matrix LaTeX: \,\Xi\!\in\!\mathbb{R}^{1024\times1024}\, having three out of every four consecutive columns discarded.

Notation LaTeX: \mbox{vec}\,X denotes vectorization; it means the columns of LaTeX: \,X are stacked with column 1 on top and column 256 on the bottom.

Matrix LaTeX: A\in\mathbb{R}^{10565\times262144} is sparse having only 979,444 nonzeros. It contains integers from the set LaTeX: \{{-1},0,1,2\}\,.

Vector LaTeX: b\, is quite sparse having only a single nonzero entry: LaTeX: 1\,.

A good presolver can eliminate about 50,000 columns of LaTeX: \,A because one of the constraints (fifth row from the bottom of LaTeX: \,A\,) has only nonnegative entries. This means that about 50,000 entries in permutation submatrix LaTeX: X\, can be set to zero before solution begins.

--Dattorro 03:31, 5 November 2010 (PDT)

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