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2009

SET: an algorithm for consistent matrix completion

Dai, Wei, Milenkovic, Olgica

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A new algorithm, termed subspace evolution and transfer (SET), is proposed for solving the consistent matrix completion problem.

In this setting, one is given a subset of the entries of a low-rank matrix, and asked to find one low-rank matrix consistent with the given observations.
We show that this problem can be solved by searching for a column space that matches the observations.
The corresponding algorithm consists of two parts -- subspace evolution and subspace transfer.

SET: an algorithm for consistent matrix completion · Around

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Academic Press, 1982
P. E. Gill, W. Murray, and M. H. Wright, Practical Optimization · 1982
Earlier work this paper cites.
A. Edelman, T. Arias, S. T. Smith, Steven, and T. Smith, “The geometry of algorithms with orthogonality constraints,” SIAM Journal on Matrix Analysis and Applications
1999
Earlier work this paper cites.
J. Cai, E. J. Candes, and Z. Shen, “A singular value thresholding algorithm for matrix completion,” Oct. 2008
2008
Earlier work this paper cites.
E. Candes and B. Recht, “Exact matrix completion via convex optimization,” Submitted for publication
2008
Earlier work this paper cites.

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Then

E. J. Candes and T. Tao, “The power of convex relaxation: Near-optimal matrix completion,” Mar. 2009
2009
Closest in time.
W. Dai and O. Milenkovic, “Subspace pursuit for compressive sensing signal reconstruction,” IEEE Trans. Inform. Theory
2009
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D. Needell and J. A. Tropp, “CoSaMP: Iterative signal recovery from incomplete and inaccurate samples,” Applied and Computational Harmonic Analysis
2009
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