User talk:Wotao.yin

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For your purposes, it may arbitrarily be set to <math>\mathbf{0}</math> or <math>\mathbf{1}</math>.
For your purposes, it may arbitrarily be set to <math>\mathbf{0}</math> or <math>\mathbf{1}</math>.
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Rectangular submatrix <math>\,X\!\in\mathbb{R}^{1024\times256}\,</math> comes from a square permutation matrix <math>\,\Xi\!\in\mathbb{R}^{1024\times1024}\,</math> having three out of every consecutive four columns discarded.
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Rectangular submatrix <math>\,X\!\in\mathbb{R}^{1024\times256}\,</math> comes from a permutation matrix <math>\,\Xi\!\in\!\mathbb{R}^{1024\times1024}\,</math> having three out of every four consecutive columns discarded.
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Notation <math>\mbox{vec}\,X</math> denotes vectorization; it means the columns of <math>\,X</math> are stacked with column 1 on top and column 256 on the bottom.
Matrix <math>A\in\mathbb{R}^{10565\times262144}</math> is sparse having only 979,444 nonzeros.
Matrix <math>A\in\mathbb{R}^{10565\times262144}</math> is sparse having only 979,444 nonzeros.
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It contains integers from the set <math>\{-1,0,1,2\}</math>.
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It contains integers from the set <math>\{{-1},0,1,2\}\,</math>.
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Vector <math>b\,</math> is quite sparse having only a single nonzero entry.
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Vector <math>b\,</math> is quite sparse having only a single nonzero entry: <math>1\,</math>.
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A good presolver can eliminate about 60,000 columns of <math>A\,</math> because one of the constraints (fifth row from the bottom) has all nonnegative entries. This means that about 60,000 entries in permutation submatrix <math>X\,</math> can be set to zero before solution begins.
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A good presolver can eliminate about 50,000 columns of <math>\,A</math> because one of the constraints '''('''fifth row from the bottom of <math>\,A\,</math>''')''' has only nonnegative entries. This means that about 50,000 entries in permutation submatrix <math>X\,</math> can be set to zero before solution begins.
--[[User:Dattorro|Dattorro]] 03:31, 5 November 2010 (PDT)
--[[User:Dattorro|Dattorro]] 03:31, 5 November 2010 (PDT)

Revision as of 03:57, 5 November 2010

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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