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https://issues.apache.org/jira/browse/MATH-924?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Luc Maisonobe resolved MATH-924.
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Resolution: Fixed
Fix Version/s: 3.1.1
Fixed in subversion repository as of r1426616.
> new multivariate vector optimizers cannot be used with large number of weights
> ------------------------------------------------------------------------------
>
> Key: MATH-924
> URL: https://issues.apache.org/jira/browse/MATH-924
> Project: Commons Math
> Issue Type: Bug
> Reporter: Luc Maisonobe
> Priority: Critical
> Fix For: 3.1.1
>
>
> When using the Weigth class to pass a large number of weights to multivariate
> vector optimizers, an nxn full matrix is created (and copied) when a n
> elements vector is used. This exhausts memory when n is large.
> This happens for example when using curve fitters (even simple curve fitters
> like polynomial ones for low degree) with large number of points. I
> encountered this with curve fitting on 41200 points, which created a matrix
> with 1.7 billion elements.
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