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… (More)
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2018
2018
In this paper, the first two terms on the right-hand side of the Broyden–Fletcher–Goldfarb–Shanno update are scaled with a… (More)
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2017
2017
Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical… (More)
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2015
2015
The introduction of quasi-Newton and nonlinear conjugate gradient methods revolutionized the field of nonlinear optimization. The… (More)
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2015
2015
This paper develops and analyzes a generalization of the Broyden class of quasiNewton methods to the problem of minimizing a… (More)
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2011
2011
Problem statement: The Maximum Likelihood Estimation (MLE) technique is the most efficient statistical approach to estimate… (More)
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2006
2006
The Broyden-Fletcher-Goldfarh-Shanno (BFGS) optimization algorithm usually used for nonlinear least squares is presented and is… (More)
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Highly Cited
2003
Highly Cited
2003
The Rprop algorithm proposed by Riedmiller and Braun is one of the best performing -rst-order learning methods for neural… (More)
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Highly Cited
1995
Highly Cited
1995
An algorithm for solving large nonlinear optimization problems with simple bounds is de scribed It is based on the gradient… (More)
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Highly Cited
1994
Highly Cited
1994
L-BFGS-B is a limited-memory algorithm for solving large nonlinear optimization problems subject to simple bounds on the… (More)
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Highly Cited
1993
Highly Cited
1993
A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm… (More)
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