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An iterative projections algorithm for ML factor analysis

Seghouane, Abd-Krim

Description

Alternating minimization of the infonnation divergence is used to derive an effective algorithm for maximum likelihood (ML) factor analysis. The proposed algorithm is derived as an iterative alternating projections procedure on a model family of probability distributions defined on the factor analysis model and a desired family of probability distributions constrained to be concentrated on the observed data. The algorithm presents the advantage of being simple to implement and stable to...[Show more]

dc.contributor.authorSeghouane, Abd-Krim
dc.contributor.editorConference Program Committee
dc.coverage.spatialCancun Mexico
dc.date.accessioned2015-12-10T22:14:21Z
dc.date.createdOctober 16-19 2008
dc.identifier.isbn9781424423750
dc.identifier.urihttp://hdl.handle.net/1885/50255
dc.description.abstractAlternating minimization of the infonnation divergence is used to derive an effective algorithm for maximum likelihood (ML) factor analysis. The proposed algorithm is derived as an iterative alternating projections procedure on a model family of probability distributions defined on the factor analysis model and a desired family of probability distributions constrained to be concentrated on the observed data. The algorithm presents the advantage of being simple to implement and stable to converge. A simulation example that illustrates the effectiveness of the proposed algorithm for ML factor analysis is presented.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE Workshop on Machine Learning for Signal Processing 2008
dc.sourceProceedings of IEEE Workshop on Machine Learning for Signal Processing 2008
dc.subjectKeywords: Alternating minimizations; Alternating projections; Effective algorithms; Factor analysis; Factor analysis models; Observed datums; Simulation examples; Image segmentation; Learning systems; Maximum likelihood; Maximum likelihood estimation; Probability;
dc.titleAn iterative projections algorithm for ML factor analysis
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2008
local.identifier.absfor090609 - Signal Processing
local.identifier.ariespublicationu4334215xPUB200
local.type.statusPublished Version
local.contributor.affiliationSeghouane, Abd-Krim, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage333
local.bibliographicCitation.lastpage338
local.identifier.doi10.1109/MLSP.2008.4685502
dc.date.updated2016-02-24T10:59:03Z
local.identifier.scopusID2-s2.0-58049149227
CollectionsANU Research Publications

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