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From: skh@nl.cs.cmu.edu (Steve Handerson)
Newsgroups: sci.math.stat,sci.math.num-analysis,sci.math,comp.sources.wanted,alt.sources.wanted
Subject: *Approximate* sing val decomp needed
Keywords: eigenvalues singular value decomposition
Message-ID: <10517@pt.cs.cmu.edu>
Date: 19 Sep 90 21:43:33 GMT
Organization: Carnegie-Mellon University, CS/RI
Lines: 28

Folks,

I've discovered what I really need is something referred to/invented by 
Harshman, R.A. and Lundy, M.E. in PARAFAC, 
or another algorithm that finds an approximate decomposition
using only the K largest eigenvalues.

Sorry if people are getting tired of this, but
I'll justify it by saying anybody doing information
retrieval might want these/this reference(s).
Here are the two (very similar) references:

"Data preprocessing and the extended PARAFAC model"
in H.G.Law, C.W.Snyder, Jr., J.A.Hattie, and R.P.McDonald (Eds) 
"Research Methods for Multimode Data Analysis", Praeger, 1984b.

"The PARAFAC model for three-way factor analysis and multi-dimensional
scaling"
in same, 1984a.

Thanks everyone for the response to my SVD post.
I'm sure I have at least two working copies of code to choose from.
[Most people pointed out Numerical Recipes, 
 but I also got a converted LINPACK routine and 
 a reference to a supposedly faster R-SVD algorithm due to Chan]
It's just that the algorithms tend to be K cubed...

-- Steve