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CGIHT: Conjugate Gradient Iterative Hard Thresholding for Compressed Sensing and Matrix Completion

Abstract:

We introduce the Conjugate Gradient Iterative Hard Thresholding (CGIHT) family of algorithms for the efficient solution of constrained underdetermined linear systems of equations arising in compressed sensing, row sparse approximation, and matrix completion. CGIHT is designed to balance the low per iteration complexity of simple hard thresholding algorithms with the fast asymptotic convergence rate of employing the conjugate gradient method. We establish provable recovery guarantees and stabi...

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Publication status:
Submitted
Peer review status:
Peer Reviewed

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Institution:
University of Oxford
Department:
Oxford, MPLS, Mathematical Inst
Role:
Author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Mathematical Inst
Role:
Author
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Funding agency for:
Tanner, J
Journal:
Information and Inference: A Journal of the IMA
URN:
uuid:52fe28b5-c53b-4611-a605-de48fd9495d6
Source identifiers:
546909
Local pid:
pubs:546909

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