[SciPy-user] L-BFGS in scipy
nwagner at iam.uni-stuttgart.de
Wed Sep 13 07:47:28 CDT 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
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
fmin_cg -- Non-linear (Polak-Ribiere) conjugate gradient
(can use function and gradient).
fmin_bfgs -- Quasi-Newton method
(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
(if you use this please quote their papers --
and I disregard fmin_l_bfgs_b because it is given in the section
Sorry for the noise.
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