Reference : Low-rank optimization for distance matrix completion
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/112432
Low-rank optimization for distance matrix completion
English
Mishra, Bamdev mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Meyer, Gilles mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Sepulchre, Rodolphe mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Dec-2011
Proceedings of the 50th IEEE Conference on Decision and Control
Yes
International
50th IEEE Conference on Decision and Control
from 12-12-2011 to 15-12-2011
[en] low-rank ; distance matrix ; matrix completion
[en] 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.
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/112432

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