UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion

dc.contributor.authorKrislock, Nathan
dc.date.accessioned2010-04-27T21:04:44Z
dc.date.available2010-04-27T21:04:44Z
dc.date.issued2010-04-27T21:04:44Z
dc.date.submitted2010
dc.description.abstractThe main result of this thesis is the development of a theory of semidefinite facial reduction for the Euclidean distance matrix completion problem. Our key result shows a close connection between cliques in the graph of the partial Euclidean distance matrix and faces of the semidefinite cone containing the feasible set of the semidefinite relaxation. We show how using semidefinite facial reduction allows us to dramatically reduce the number of variables and constraints required to represent the semidefinite feasible set. We have used this theory to develop a highly efficient algorithm capable of solving many very large Euclidean distance matrix completion problems exactly, without the need for a semidefinite optimization solver. For problems with a low level of noise, our SNLSDPclique algorithm outperforms existing algorithms in terms of both CPU time and accuracy. Using only a laptop, problems of size up to 40,000 nodes can be solved in under a minute and problems with 100,000 nodes require only a few minutes to solve.en
dc.identifier.urihttp://hdl.handle.net/10012/5093
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.subjectEuclidean distance matricesen
dc.subjectlow-rank matrix completionen
dc.subjectsemidefinite relaxationsen
dc.subjectfacial reductionen
dc.subjectwireless sensor network localizationen
dc.subjectmolecular conformationen
dc.subject.programCombinatorics and Optimizationen
dc.titleSemidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completionen
dc.typeDoctoral Thesisen
uws-etd.degreeDoctor of Philosophyen
uws-etd.degree.departmentCombinatorics and Optimizationen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Krislock_Nathan.pdf
Size:
2.55 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
251 B
Format:
Item-specific license agreed upon to submission
Description: