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A semismooth newton method for the nearest Euclidean distance matrix problem

Qi, Houduo (2013) A semismooth newton method for the nearest Euclidean distance matrix problem. SIAM Journal on Matrix Analysis and Applications, 34 (1), 67-93.

Record type: Article

Abstract

The Nearest Euclidean distance matrix problem (NEDM) is a fundamental
computational problem in applications such as
multidimensional scaling and molecular
conformation from nuclear magnetic resonance data in computational chemistry.
Especially in the latter application, the problem is often large scale with the number of
atoms ranging from a few hundreds to a few thousands.
In this paper, we introduce a
semismooth Newton method that solves the dual problem of (NEDM). We prove that the
We then present an application of the Newton method to NEDM with $H$-weights.
We demonstrate the superior performance of the Newton method over existing methods
including the latest quadratic semi-definite programming solver.
This research also opens a new avenue towards efficient solution methods for the molecular
embedding problem.

Text
084952RRRR.pdf - Author's Original

Published date: 2013
Organisations: Operational Research

Identifiers

Local EPrints ID: 347784
URI: http://eprints.soton.ac.uk/id/eprint/347784
ISSN: 0895-4798
ORCID for Houduo Qi: orcid.org/0000-0003-3481-4814

Catalogue record

Date deposited: 31 Jan 2013 14:03

Contributors

Author: Houduo Qi