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Semi-supervised structuring of complex data

Rizoiu, Marian-Andrei

Description

The objective of the thesis is to explore how complex data can be treated using unsupervised machine learning techniques, in which additional information is injected to guide the exploratory process. Starting from specific problems, our contributions take into account the different dimensions of the complex data: their nature (image, text), the additional information attached to the data (labels, structure, concept ontologies) and the temporal dimension. A special attention is given to data...[Show more]

dc.contributor.authorRizoiu, Marian-Andrei
dc.coverage.spatialBeijing China
dc.date.accessioned2018-11-30T01:19:46Z
dc.date.available2018-11-30T01:19:46Z
dc.date.createdAugust 3-9 2013
dc.identifier.isbn9781577356332
dc.identifier.urihttp://hdl.handle.net/1885/154181
dc.description.abstractThe objective of the thesis is to explore how complex data can be treated using unsupervised machine learning techniques, in which additional information is injected to guide the exploratory process. Starting from specific problems, our contributions take into account the different dimensions of the complex data: their nature (image, text), the additional information attached to the data (labels, structure, concept ontologies) and the temporal dimension. A special attention is given to data representation and how additional information can be leveraged to improve this representation.
dc.format.mimetypeapplication/pdf
dc.publisherAAAI Press
dc.relation.ispartofseries23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
dc.sourceIJCAI International Joint Conference on Artificial Intelligence
dc.source.urihttp://ijcai.org/papers13/contents.php
dc.subjectKeywords: Complex data; Data representations; Semi-supervised; Specific problems; Temporal dimensions; Unsupervised machine learning; Artificial intelligence; Learning systems
dc.titleSemi-supervised structuring of complex data
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2013
local.identifier.absfor080201 - Analysis of Algorithms and Complexity
local.identifier.ariespublicationa383154xPUB3891
local.type.statusPublished Version
local.contributor.affiliationRizoiu, Marian-Andrei, College of Engineering and Computer Science, ANU
local.bibliographicCitation.startpage3239
local.bibliographicCitation.lastpage3240
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2018-11-29T08:22:19Z
local.identifier.scopusID2-s2.0-84896064319
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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