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Sparse exploratory factor analysis

Fontanella, Sara; Trendafilov, Nickolay and Adachi, Kohei (2014). Sparse exploratory factor analysis. In: Proceedings of COMPSTAT 2014: 21st International Conference on Computational Statistics, pp. 281–288.

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Sparse principal component analysis is a very active research area in the last decade. In the same time, there are very few works on sparse factor analysis. We propose a new contribution to the area by exploring a procedure for sparse factor analysis where the unknown parameters are found simultaneously.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 The International Statistical Institute/International Association for Statistical Computing
ISBN: 2-8399-1347-X, 978-2-8399-1347-8
Project Funding Details:
Funded Project NameProject IDFunding Body
Sparse factor analysis with application to large data setsRPG--2013--211Leverhulme Trust
Keywords: ℓ1 penalties; matrix manifolds; projected gradients
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 41226
Depositing User: Nickolay Trendafilov
Date Deposited: 04 Nov 2014 11:05
Last Modified: 08 Dec 2018 16:00
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