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:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||15 Dec 2015 13:03|
|Last Modified:||10 Feb 2016 01:32|