CUED Publications database

Low-rank optimization for distance matrix completion

Mishra, B and Meyer, G and Sepulchre, R (2011) Low-rank optimization for distance matrix completion. In: UNSPECIFIED pp. 4455-4460..

Full text not available from this repository.


This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. The resulting algorithms scale to high-dimensional problems and monotonically converge to a global solution of the problem. Finally, numerical experiments illustrate the good performance of the proposed algorithms on benchmarks. © 2011 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:15
Last Modified: 09 Sep 2021 01:36
DOI: 10.1109/CDC.2011.6160810