Skip navigation
Skip navigation

An iterative projections algorithm for ML factor analysis

Seghouane, Abd-Krim


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]

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
Source: Proceedings of IEEE Workshop on Machine Learning for Signal Processing 2008
DOI: 10.1109/MLSP.2008.4685502


File Description SizeFormat Image
01_Seghouane_An_iterative_projections_2008.pdf865.84 kBAdobe PDFThumbnail
02_Seghouane_An_iterative_projections_2008.pdf199.57 kBAdobe PDFThumbnail

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator