[SciPy-user] L-BFGS in scipy
Nils Wagner
nwagner at iam.uni-stuttgart.de
Wed Sep 13 08:47:28 EDT 2006
Robert Kern wrote:
> Nils Wagner wrote:
>
>> Hi all,
>>
>> Has someone implemented the limited memory BFGS method in scipy ?
>>
>
> Yes. scipy.optimize.fmin_l_bfgs_b(). Please grep for these things.
>
>
Thank you Robert.
If bounds=None we have an unconstraint version.
Thus fmin_l_bfgs_b is also an unconstrained optimizer. I missed that.
Maybe fmin_l_bfgs_b should also be added to the list of general-purpose
optimization routines
help (optimize) yields
A collection of general-purpose optimization routines.
fmin -- Nelder-Mead Simplex algorithm
(uses only function calls)
fmin_powell -- Powell's (modified) level set method (uses only
function calls)
fmin_cg -- Non-linear (Polak-Ribiere) conjugate gradient
algorithm
(can use function and gradient).
fmin_bfgs -- Quasi-Newton method
(Broydon-Fletcher-Goldfarb-Shanno);
(can use function and gradient)
fmin_ncg -- Line-search Newton Conjugate Gradient (can use
function, gradient and Hessian).
leastsq -- Minimize the sum of squares of M equations in
N unknowns given a starting estimate.
Constrained Optimizers (multivariate)
fmin_l_bfgs_b -- Zhu, Byrd, and Nocedal's L-BFGS-B constrained
optimizer
(if you use this please quote their papers --
see help)
and I disregard fmin_l_bfgs_b because it is given in the section
Constrained Optimizers.
Sorry for the noise.
Nils
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