Estimating labels from label proportions

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dc.contributor.authorQuadrianto, Novi
dc.contributor.authorSmola, Alexander
dc.contributor.authorCaetano, Tiberio
dc.contributor.authorLe, Quoc Viet
dc.date.accessioned2015-12-10T22:38:23Z
dc.date.issued2009
dc.date.updated2016-02-24T11:44:28Z
dc.description.abstractConsider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known label proportions. This problem appears in areas like e-commerce, spam filtering and improper content detection. We present consistent estimators which can reconstruct the correct labels with high probability in a uniform convergence sense. Experiments show that our method works well in practice.
dc.identifier.issn1532-4435
dc.identifier.urihttp://hdl.handle.net/1885/56738
dc.publisherMIT Press
dc.sourceJournal of Machine Learning Research
dc.source.urihttp://jmlr.csail.mit.edu/papers/v10
dc.subjectKeywords: Consistent estimators; Content detections; E commerces; Following problems; High probabilities; Spam filtering; Uniform convergences; Electronic commerce; Learning systems; Robot learning; Labels
dc.titleEstimating labels from label proportions
dc.typeJournal article
local.bibliographicCitation.issueOct
local.bibliographicCitation.lastpage2374
local.bibliographicCitation.startpage2349
local.contributor.affiliationQuadrianto, Novi, College of Engineering and Computer Science, ANU
local.contributor.affiliationSmola, Alexander, Yahoo! Research
local.contributor.affiliationCaetano, Tiberio, College of Engineering and Computer Science, ANU
local.contributor.affiliationLe, Quoc Viet, Stanford University
local.contributor.authoremailu4590840@anu.edu.au
local.contributor.authoruidQuadrianto, Novi, u4361150
local.contributor.authoruidCaetano, Tiberio, u4590840
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationu8803936xPUB373
local.identifier.citationvolume10
local.identifier.scopusID2-s2.0-56549100468
local.identifier.uidSubmittedByu8803936
local.type.statusPublished Version

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