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Posted to issues@commons.apache.org by "Gilles (JIRA)" <ji...@apache.org> on 2012/12/29 14:18:12 UTC

[jira] [Commented] (MATH-924) new multivariate vector optimizers cannot be used with large number of weights

    [ https://issues.apache.org/jira/browse/MATH-924?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13540904#comment-13540904 ] 

Gilles commented on MATH-924:
-----------------------------

Changes committed in revision 1426758.

The same problem would occur int the deprecated "o.a.c.m.optimization" package. The same changes must be ported there.

                
> 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
>
>         Attachments: MATH-924
>
>
> 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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