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gptkbp:instanceOf
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mathematical optimization
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gptkbp:abbreviation
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Limited-memory Broyden–Fletcher–Goldfarb–Shanno
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gptkbp:advantage
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low memory requirement
efficient for high-dimensional problems
less accurate Hessian approximation
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gptkbp:category
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gptkb:logic
gradient-based optimization
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gptkbp:compatibleWith
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full Hessian matrix
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gptkbp:developedBy
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gptkb:Jorge_Nocedal
gptkb:Dong_C._Liu
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gptkbp:estimatedCost
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inverse Hessian matrix
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gptkbp:firstPublished
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1989
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gptkbp:fullName
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gptkb:Limited-memory_Broyden–Fletcher–Goldfarb–Shanno_algorithm
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https://www.w3.org/2000/01/rdf-schema#label
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LBFGS
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gptkbp:implementedIn
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gptkb:TensorFlow
gptkb:Julia
gptkb:MATLAB
gptkb:PyTorch
gptkb:SciPy
R
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gptkbp:memoryUsage
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limited
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gptkbp:publishedIn
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gptkb:Mathematical_Programming
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gptkbp:referencePaper
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Nocedal, J. (1980). Updating quasi-Newton matrices with limited storage. Mathematics of Computation.
Liu, D. C., & Nocedal, J. (1989). On the limited memory BFGS method for large scale optimization. Mathematical Programming.
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gptkbp:relatedTo
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gptkb:BFGS_algorithm
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gptkbp:supportsAlgorithm
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gptkb:quasi-Newton_method
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gptkbp:usedFor
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unconstrained optimization
large-scale optimization
numerical optimization
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gptkbp:usedIn
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gptkb:machine_learning
data science
scientific computing
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gptkbp:bfsParent
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gptkb:NLopt
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gptkbp:bfsLayer
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8
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