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Coverage Optimized Active Learning for k − NN Classifiers

dc.contributor.authorJoshi, Ajay J.
dc.contributor.authorPorikli, Fatih
dc.contributor.authorPapanikolopoulos, Nikolaos
dc.coverage.spatialSaint Paul USA
dc.date.accessioned2015-12-08T22:14:41Z
dc.date.createdMay 14-18 2012
dc.identifier.urihttp://hdl.handle.net/1885/30373
dc.publisherIEEE Robotics and Automation Society
dc.relation.ispartofseriesIEEE International Conference on Robotics and Automation 2012
dc.subjectKeywords: Active Learning; Active-learning algorithm; Data points; K-nearest neighbors; k-NN classifier; Large datasets; Locality sensitive hashing; Maximum distance; Nearest neighbors; Orders of magnitude; Robotics applications; Submodular functions; Training budg
dc.titleCoverage Optimized Active Learning for k − NN Classifiers
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2012
local.identifier.absfor090602 - Control Systems, Robotics and Automation
local.identifier.ariespublicationu4628727xPUB73
local.type.statusPublished Version
local.contributor.affiliationJoshi, Ajay J., University of Minnesota
local.contributor.affiliationPorikli, Fatih, College of Engineering and Computer Science, ANU
local.contributor.affiliationPapanikolopoulos, Nikolaos, University of Minnesota
local.description.embargo2037-12-31
local.bibliographicCitation.startpage5353
local.bibliographicCitation.lastpage5358
local.identifier.doi10.1109/ICRA.2012.6225054
local.identifier.absseo970109 - Expanding Knowledge in Engineering
dc.date.updated2016-06-14T09:06:52Z
local.identifier.scopusID2-s2.0-84864428377
CollectionsANU Research Publications

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