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From Bruce A Johnson <johns...@umbc.edu>
Subject Re: [math] NonLinearConjugateGradientOptimizer line search
Date Thu, 27 Feb 2014 02:18:01 GMT
On Feb 26, 2014, at 6:23 PM, Bruce A Johnson <johnsonb@umbc.edu> wrote:

> The NonLinearConjugateGradientOptimizer does a line search for a zero in the gradient
(see comment from source below), rather than a search for a minimum of the function (the latter
is what is used in Numerical Recipes and in the simple discussion on Wikipedia ( http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method).
 Is this wise?  It seems a clever idea, but  in a complicated surface with numerical errors
the zero in the gradient may not be at a function minimum and the algorithm could be a deoptimizer.
 I ask because (in a problem too complex too easily reproduce) I'm sometimes getting junk
as output of this routine.
> 
> Bruce
> 
> Comment for the LIneSearchFunction
> 
> 350     * The function represented by this class is the dot product of
> 351     * the objective function gradient and the search direction. Its
> 352     * value is zero when the gradient is orthogonal to the search
> 353     * direction, i.e. when the objective function value is a local
> 354     * extremum along the search direction.

Just realized, in reviewing all open bugs, that this has already been reported as Math-1092
( https://issues.apache.org/jira/browse/MATH-1092 )

I agree with the assignment priority, this is a Major bug.

Bruce


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