Yea, I realize there were a lot of questions, Ian, but I tried to make
them as concise as possible. And since there are quite a few with no
answers, I'll assume they were good questions!? Generally this list is
my last stop in the investigation, so if there is no reply odds are I
haven't figured it out! I'll look back and make sure I haven't
answered any and I'll post solutions if I did. I'll check with the
netlib people on these optimization issues.
Thanks,
David
On Tue, Feb 17, 2009 at 5:24 AM, Ian Scott
<ian.m.scott@...> wrote:
> I'm sorry you are having problems with the optimisers.
>
> I can't see anything wrong with your example code in either this of the
> constrained case. However, given my experience with the various optimisers
> (lbfgs included) I would investigate without ruling out the possibility that
> the optimisers are working correctly.
>
> I am afraid that you may not get much help from VXL regarding detailed
> problems with the optimisers. VXL just provides a wrappers around the well
> known routines that are published in the netlib repository. You might be
> able to get some help from a netlib mailing list  although I've never tried
> myself.
>
> If you have detailed problems with the optimisers, you will usually need to
> debug them yourself. If you do find any specific bug in the optimisers, we
> would be delighted to receive a patch.
>
> Finally, whilst the quality of your emails is comparatively high for new vxl
> users, there are rather a lot of them. As per
> http://vxl.sourceforge.net/vxluserspolicy.html it might be useful to know
> which of your previous problems have been solved or bypassed.
>
> Sorry I can't be more help with this particular problem.
> Ian.
>
> David Doria wrote:
>>
>> I am using lbfgs to minimize a function in 1D (later to be expanded to
>> more dimensions). It seems like after only 3 iterations, it converges.
>> However, it just keeps going until it hits the iteration limit and
>> then fails.
>>
>> I set it up with these params:
>> vnl_lbfgs Minimizer(Cost);
>> Minimizer.set_verbose(true);
>> Minimizer.set_f_tolerance(1e2);//when difference in function value in
>> successive iterations is at least this small, stop.
>> Minimizer.set_x_tolerance(1e2);//when steps are at least this small,
>> stop.
>> Minimizer.set_epsilon_function(1e3); //finite difference step length
>> Minimizer.default_step_length = 1e1;
>> Minimizer.set_max_function_evals(10);
>>
>> And this is the output:
>>
>> vnl_lbfgs: n = 1, memory = 5, Workspace = 21[ 0.000160217 MB],
>> ErrorScale = 1, xnorm = 0
>> Iter 1, Eval 1: Best F = 103879
>> *************************************************
>> N=1 NUMBER OF CORRECTIONS=5 INITIAL VALUES F= 103879 GNORM=
>> 172625
>> *************************************************
>> I NFN FUNC GNORM STEPLENGTH
>> Iter 2, Eval 2: Best F = 103879
>> 1 3 65313.580 2765.688 0.000
>> Iter 3, Eval 3: Best F = 65313.6
>> Iter 4, Eval 4: Best F = 65313.6
>> Iter 5, Eval 5: Best F = 65313.6
>> Iter 6, Eval 6: Best F = 65313.6
>> Iter 7, Eval 7: Best F = 65313.6
>> Iter 8, Eval 8: Best F = 65313.6
>> Iter 9, Eval 9: Best F = 65313.6
>> Iter 10, Eval 10: Best F = 65313.6
>>
>> vnl_lbfgs: Error. Netlib routine lbfgs failed.
>> IFLAG= 1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH
>> ERROR RETURN OF LINE SEARCH: INFO= 6 POSSIBLE CAUSES: FUNCTION OR
>> GRADIENT ARE INCORRECT OR INCORRECT TOLERANCES
>>
>>
>> These iterations are different than the "minimizer iterations", right?
>> They are the line search iterations. Is this problem something that is
>> tuned with the line_search_accuracy variable? I didn't understand what
>> the values were? It said set it to .1 if the function evaluations are
>> cheap (they are not, they take 1 minute each), or .9 is the default.
>> What is the meaning of these values?
>>
>>
>> Thanks,
>>
>> David
>>
>>
>> 
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