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Broyden–Fletcher–Goldfarb–Shanno algorithm

Known as: BFGS, Broydon-Fletcher-Goldfarb-Shanno, BFGS method 
In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear… 
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Related topics

Related topics

25 relations
Approximation theoryBerndt–Hall–Hall–Hausman algorithmBroyden's methodDavidon–Fletcher–Powell formula

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Channel Estimation for Residual Self-Interference in Full-Duplex Amplify-and-Forward Two-Way Relays
Training schemes for full duplex two-way relays are investigated. We propose a novel one-block training scheme with a maximum… 
2012
2012
Broyden-Fletcher-Goldfarb-Shanno algorithm based on new quasi-Newton equation
Based on the error analysis of the Taylor expansion,a new model for improving the quadratic model is put forward,and the new… 
Highly Cited
2007
Highly Cited
2007
Exponentiated gradient algorithms for log-linear structured prediction
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these… 
2004
2004
OPTIMIZATION OF TRANSIENT HEATER SETTINGS TO PROVIDE SPATIALLY UNIFORM HEATING IN MANUFACTURING PROCESSES INVOLVING RADIANT HEATING
This article presents an optimization methodology for finding the heater settings that provide spatially uniform transient… 
2001
2001
Design of linear phase IIR filters via weighted least-squares approximation
A new method for designing IIR digital filters with linear phase in the passband is proposed. This method is based on frequency… 
1999
1999
A Variable Memory Quasi-Newton Training Algorithm
A new neural network training algorithm which optimises performance in relation to the available memory is described. Numerically… 
1997
1997
Nonlinear PLS modelling using radial basis functions
An approach to nonlinear partial least squares (PLS) modelling using radial basis function (RBF) neural networks to provide a… 
1990
1990
Deriving collinear scaling algorithms as extensions of quasi-Newton methods and the local convergence of DFP- and BFGS-related collinear scaling algorithms
This paper is concerned with collinear scaling algorithms for unconstrained minimization where the underlying local approximants… 
1989
1989
Nonlinear parameter estimation experiments for static load modelling in electric power systems
In the paper, we consider the problem of estimating the parameters of static power system load models intended for use in load… 
Highly Cited
1986
Highly Cited
1986
A general-purpose optimization program for engineering design
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