Statements (32)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
mathematical optimization
|
| gptkbp:application |
gptkb:machine_learning
computational physics data science engineering optimization |
| gptkbp:category |
gptkb:logic
gradient-based optimization |
| gptkbp:citation |
gptkb:TensorFlow
gptkb:MATLAB gptkb:PyTorch gptkb:SciPy R |
| gptkbp:developedBy |
gptkb:Jorge_Nocedal
gptkb:Dong_C._Liu |
| gptkbp:feature |
approximates inverse Hessian matrix
suitable for high-dimensional problems uses limited memory |
| gptkbp:fullName |
Limited-memory Broyden–Fletcher–Goldfarb–Shanno method
|
| https://www.w3.org/2000/01/rdf-schema#label |
L-BFGS method
|
| gptkbp:input |
objective function
gradient of objective function |
| gptkbp:introducedIn |
1980s
|
| gptkbp:output |
local minimum
|
| gptkbp:relatedTo |
gptkb:BFGS_method
|
| gptkbp:supportsAlgorithm |
gptkb:quasi-Newton_method
|
| gptkbp:usedFor |
unconstrained optimization
large-scale optimization numerical optimization |
| gptkbp:bfsParent |
gptkb:M.J.D._Powell
gptkb:L-BFGS-B_method gptkb:quasi-Newton_method |
| gptkbp:bfsLayer |
8
|