|
gptkbp:instanceOf
|
gptkb:quasi-Newton_method
mathematical optimization
|
|
gptkbp:compatibleWith
|
second derivatives
|
|
gptkbp:estimatedCost
|
gptkb:Hessian_matrix
|
|
gptkbp:fasterThan
|
steepest descent
|
|
gptkbp:firstPublished
|
1970
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
BFGS algorithm
|
|
gptkbp:implementedIn
|
gptkb:Dakota
gptkb:SAS
gptkb:TensorFlow
gptkb:Wolfram_Mathematica
gptkb:Julia
gptkb:MATLAB
gptkb:SPSS
gptkb:KNITRO
gptkb:Maple
gptkb:GSL
gptkb:PyTorch
gptkb:Stata
gptkb:Optimus
gptkb:SciPy
gptkb:COBYLA
gptkb:Octave
gptkb:OptiX
gptkb:NLopt
gptkb:OpenMDAO
gptkb:pyOpt
gptkb:CVXPY
gptkb:Excel_Solver
gptkb:Ipopt
gptkb:NLsolve.jl
gptkb:OpenOpt
gptkb:OpenTURNS
gptkb:Opt4J
gptkb:Opti
gptkb:OptiCore
gptkb:OptiDesign
gptkb:OptiEngine
gptkb:OptiFlow
gptkb:OptiKit
gptkb:OptiLab
gptkb:OptiMath
gptkb:OptiMax
gptkb:OptiPro
gptkb:OptiSim
gptkb:OptiSoft
gptkb:OptiSolve
gptkb:OptiSuite
gptkb:OptiTools
gptkb:Opti_Toolbox
gptkb:Optim.jl
gptkb:Optunity
gptkb:cvxopt
gptkb:cvxpy
gptkb:nloptr
gptkb:optimx
gptkb:pyOptSparse
gptkb:Optuna
gptkb:JuMP
gptkb:OptiStruct
R
C++ libraries
fmincon
fminunc
minimize
Fortran libraries
fmin_bfgs
fminsearch
jax.scipy.optimize.minimize
minpack
nlm
nlminb
optim
optimise
optimise.minimize
pyomo
scipy.optimize.minimize
tensorflow_probability.optimizer.lbfgs_minimize
torch.optim.LBFGS
|
|
gptkbp:isGradientBased
|
true
|
|
gptkbp:isIterative
|
true
|
|
gptkbp:isSecondOrder
|
false
|
|
gptkbp:namedAfter
|
gptkb:Fletcher
gptkb:Broyden
gptkb:Goldfarb
gptkb:Shanno
|
|
gptkbp:relatedTo
|
gptkb:L-BFGS_algorithm
DFP algorithm
|
|
gptkbp:requires
|
gradient of objective function
|
|
gptkbp:updated
|
inverse Hessian matrix
|
|
gptkbp:used_in
|
gptkb:machine_learning
engineering
statistics
numerical optimization
|
|
gptkbp:usedFor
|
unconstrained nonlinear optimization
|
|
gptkbp:bfsParent
|
gptkb:L-BFGS-B
gptkb:scipy.optimize
|
|
gptkbp:bfsLayer
|
7
|