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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.
2020
2020
An Efficient Single-Parameter Scaling Memoryless Broyden-Fletcher-Goldfarb-Shanno Algorithm for Solving Large Scale Unconstrained Optimization Problems
In this paper, a new spectral scaling memoryless Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is developed for solving large… 
2017
2017
Hidden Markov random field model and Broyden–Fletcher–Goldfarb–Shanno algorithm for brain image segmentation
Abstract Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of… 
Highly Cited
2017
Highly Cited
2017
Real-Time Optimal Power Flow
Future power networks are expected to incorporate a large number of distributed energy resources, which introduce randomness and… 
Highly Cited
2014
Highly Cited
2014
A Modified Self-Scaling Memoryless Broyden–Fletcher–Goldfarb–Shanno Method for Unconstrained Optimization
The introduction of quasi-Newton and nonlinear conjugate gradient methods revolutionized the field of nonlinear optimization. The… 
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
Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem
Nonnegative Matrix Approximation is an effective matrix decomposition technique that has proven to be useful for a wide variety… 
2006
2006
An Improved Learning Algorithm Based on The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Method For Back Propagation Neural Networks
The Broyden-Fletcher-Goldfarh-Shanno (BFGS) optimization algorithm usually used for nonlinear least squares is presented and is… 
Highly Cited
2006
Highly Cited
2006
A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix
The nearest correlation matrix problem is to find a correlation matrix which is closest to a given symmetric matrix in the… 
Highly Cited
2006
Highly Cited
2006
Accelerated training of conditional random fields with stochastic gradient methods
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of… 
Highly Cited
2002
Highly Cited
2002
Convergence Properties of the BFGS Algoritm
The BFGS method is one of the most famous quasi-Newton algorithms for unconstrained optimization. In 1984, Powell presented an… 
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