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Matrix completion under interval uncertainty
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DOI：10.1016/j.ejor.2016.07.014.png)
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Abstract
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Matrix completion under interval uncertainty can be cast as a matrix completion problem with element wise box constraints. We present an efficient alternating-direction parallel coordinate-descent method for the problem. We show that the method outperforms any other known method on a benchmark in image in-painting in terms of signal-to-noise ratio, and that it provides high-quality solutions for an instance of collaborative filtering with 100,198,805 recommendations within 5 minutes on a single personal computer. (C) 2016 The Authors. Published by Elsevier B.V.
Keywords:
Matrix completion
Robust optimization
Collaborative filtering
Coordinate descent
Large-scale optimization
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