Statements (32)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
mathematical optimization
|
| gptkbp:application |
gptkb:machine_learning
data fitting engineering design |
| gptkbp:category |
gptkb:quasi-Newton_method
|
| gptkbp:feature |
gptkb:logic
does not require explicit Hessian line search required memory intensive for large problems superlinear convergence |
| gptkbp:fullName |
gptkb:Broyden–Fletcher–Goldfarb–Shanno_algorithm
|
| https://www.w3.org/2000/01/rdf-schema#label |
BFGS
|
| gptkbp:implementedIn |
gptkb:Fortran
gptkb:Julia gptkb:C++ gptkb:MATLAB gptkb:SciPy R |
| gptkbp:input |
objective function
gradient of objective function |
| gptkbp:introducedIn |
1970
|
| gptkbp:namedAfter |
gptkb:Charles_Broyden
gptkb:David_Shanno gptkb:Donald_Goldfarb gptkb:Roger_Fletcher |
| gptkbp:output |
local minimum
|
| gptkbp:relatedTo |
gptkb:L-BFGS
DFP algorithm |
| gptkbp:updated |
approximate Hessian matrix
|
| gptkbp:usedFor |
unconstrained nonlinear optimization
|
| gptkbp:bfsParent |
gptkb:SciPy_optimize.minimize
|
| gptkbp:bfsLayer |
6
|