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dc.contributor.authorCadena, J.en
dc.contributor.authorChen, F.en
dc.contributor.authorVullikanti, A. K.en
dc.coverage.spatialHouston TXen
dc.date.accessioned2017-03-06T02:17:26Zen
dc.date.available2017-03-06T02:17:26Zen
dc.date.issued2017-04-27en
dc.identifier.issn2167-0102en
dc.identifier.urihttp://hdl.handle.net/10919/75254en
dc.publisherSiamen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleNear-Optimal and Practical Algorithms for Graph Scan Statisticsen
dc.typeConference proceedingen
dc.description.versionAccepted versionen
dc.contributor.departmentComputer Scienceen
dc.contributor.departmentFralin Life Sciences Instituteen
dc.description.notesYes, full paper (Peer reviewed?)en
dc.title.serialProceedings of the ... SIAM International Conference on Data Mining. SIAM International Conference on Data Miningen
pubs.finish-date2017-04-29en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Instituteen
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Institute/Researchersen
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Institute/SelectedFaculty1en
pubs.start-date2017-04-27en


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