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Gilles commented on MATH924:

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: MATH924
> URL: https://issues.apache.org/jira/browse/MATH924
> Project: Commons Math
> Issue Type: Bug
> Reporter: Luc Maisonobe
> Priority: Critical
> Fix For: 3.1.1
>
> Attachments: MATH924
>
>
> 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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