Maximum likelihood based sparse and distributed conjoint analysis

Reference : Maximum likelihood based sparse and distributed conjoint analysis


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/7585

Title :	Maximum likelihood based sparse and distributed conjoint analysis
Language :	English
Author, co-author :	Tsakonas, Efthymios [> >]
	Jalden, Joakim [> >]
	Sidiropoulos, Nicolas D. [> >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2012
Main document title :	Statistical Signal Processing Workshop (SSP), 2012 IEEE
Publisher :	IEEE
Pages :	33 - 36
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-4673-0182-4
Event name :	Statistical Signal Processing Workshop (SSP), 2012 IEEE
Event date :	5-8 August, 2012
Event place (city) :	Ann Arbor, MI
Event country :	USA
Abstract :	[en] A new statistical model for choice-based conjoint analysis is proposed. The model uses auxiliary variables to account for outliers and to detect the salient features that influence decisions. Unlike recent classification-based approaches to choice-based conjoint analysis, a sparsity-aware maximum likelihood (ML) formulation is proposed to estimate the model parameters. The proposed approach is conceptually appealing, mathematically tractable, and is also well-suited for distributed implementation. Its performance is tested and compared to the prior state-of-art using synthetic as well as real data coming from a conjoint choice experiment for coffee makers, with very promising results.
Target :	Others
Permalink :	http://hdl.handle.net/10993/7585
DOI :	10.1109/SSP.2012.6319698

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