CUED Publications database

R3MC: A Riemannian three-factor algorithm for low-rank matrix completion

Mishra, B and Sepulchre, R (2014) R3MC: A Riemannian three-factor algorithm for low-rank matrix completion. In: UNSPECIFIED pp. 1137-1142..

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Abstract

© 2014 IEEE. We exploit the versatile framework of Riemannian optimization on quotient manifolds to develop R3MC, a nonlinear conjugate-gradient method for low-rank matrix completion. The underlying search space of fixed-rank matrices is endowed with a novel Riemannian metric that is tailored to the least-squares cost. Numerical comparisons suggest that R3MC robustly outperforms state-of-the-art algorithms across different problem instances, especially those that combine scarcely sampled and ill-conditioned data.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:34
Last Modified: 03 Aug 2017 03:07
DOI: