Rank-one matrix completion is solved by the sum-of-squares relaxation of order two

This note studies the problem of nonsymmetric rank-one matrix completion. We show that in every instance where the problem has a unique solution, one can recover the original matrix through the second round of the sum-of-squares/Lasserre hierarchy with minimization of the trace of the moments matrix...

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Bibliographic Details
Main Authors: Cosse, Augustin (Author), Demanet, Laurent (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mathematics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2017-06-26T23:18:45Z.
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Summary:This note studies the problem of nonsymmetric rank-one matrix completion. We show that in every instance where the problem has a unique solution, one can recover the original matrix through the second round of the sum-of-squares/Lasserre hierarchy with minimization of the trace of the moments matrix. Our proof system is based on iteratively building a sum of N - 1 linearly independent squares, where N is the number of monomials of degree at most two, corresponding to the canonical basis (z[superscript α] - z[subscript 0][superscript α])[superscript 2]. Those squares are constructed from the ideal I generated by the constraints and the monomials provided by the minimization of the trace.
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