About: Levenberg–Marquardt algorithm

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In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting. The LMA interpolates between the Gauss–Newton algorithm (GNA) and the method of gradient descent. The LMA is more robust than the GNA, which means that in many cases it finds a solution even if it starts very far off the final minimum. For well-behaved functions and reasonable starting parameters, the LMA tends to be slower than the GNA. LMA can also be viewed as Gauss–Newton using a trust region approach.

Attributes	Values
rdfs:label	Levenberg–Marquardt algorithm (en)
rdfs:comment	In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting. The LMA interpolates between the Gauss–Newton algorithm (GNA) and the method of gradient descent. The LMA is more robust than the GNA, which means that in many cases it finds a solution even if it starts very far off the final minimum. For well-behaved functions and reasonable starting parameters, the LMA tends to be slower than the GNA. LMA can also be viewed as Gauss–Newton using a trust region approach. (en)
sameAs	Levenberg–Marquardt algorithm
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Cite_journal dbt:Clarify dbt:Dead_link dbt:Refbegin dbt:Refend dbt:Reflist dbt:Short_description dbt:Tmath dbt:Isbn dbt:Optimization_algorithms
Subject	Statistical algorithms Least squares Optimization algorithms and methods
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Levenberg–Marquardt_algorithm?oldid=1067650382&ns=0
Wikipage page ID	892446 (xsd:integer)
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Wikipage revision ID	1067650382 (xsd:integer)
Link from a Wikipage to another Wikipage	Frankford Arsenal Non-linear least squares Well-posed problem Statistician Statistics Tikhonov regularization Statistical algorithms Geodesic Jacobian matrix and determinant Least squares Optimization algorithms and methods Directional derivative Donald Marquardt DuPont Curve fitting Robustness (computer science) Trust region SIAM Journal on Numerical Analysis Finite difference GNU Octave Gauss–Newton algorithm Gradient Gradient descent Kenneth Levenberg Estimation theory Iteration Least squares MATLAB Mathematics Maxima and minima Nelder–Mead method Ridge regression
has abstract	In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting. The LMA interpolates between the Gauss–Newton algorithm (GNA) and the method of gradient descent. The LMA is more robust than the GNA, which means that in many cases it finds a solution even if it starts very far off the final minimum. For well-behaved functions and reasonable starting parameters, the LMA tends to be slower than the GNA. LMA can also be viewed as Gauss–Newton using a trust region approach. The algorithm was first published in 1944 by Kenneth Levenberg, while working at the Frankford Army Arsenal. It was rediscovered in 1963 by Donald Marquardt, who worked as a statistician at DuPont, and independently by Girard, Wynne and Morrison. The LMA is used in many software applications for solving generic curve-fitting problems. By using the Gauss-Newton algorithm it often converges faster than first-order methods. However, like other iterative optimization algorithms, the LMA finds only a local minimum, which is not necessarily the global minimum. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Levenberg–Marquardt_algorithm
is Wikipage redirect of	Levenberg-Marquardt Levenberg-Marquardt Method Levenberg-Marquardt nonlinear least squares fitting algorithm Levenberg Marquardt Levenberg–Marquardt Levenberg–Marquardt nonlinear least squares fitting algorithm Levenburg-Marquardt Levmar Marquardt-Levenberg algorithm Levenberg-Marquardt algorithm Damped least squares
is Link from a Wikipage to another Wikipage of	Fluorescence correlation spectroscopy List of statistics articles Non-linear least squares Adept (C++ library) Backpropagation Biryukov equation Broyden–Fletcher–Goldfarb–Shanno algorithm Bundle adjustment Gnuplot Donald Marquardt Curve fitting Hydrus (software) List of numerical analysis topics Hodgkin–Huxley model Homography (computer vision) List of algorithms Michaelis–Menten kinetics Newton's method in optimization Electrical impedance tomography Encog Fityk Fundamental matrix (computer vision) GNU Scientific Library Gauss–Newton algorithm Kenneth Levenberg Determination of equilibrium constants Inverse kinematics LM LMA Models of neural computation Low-rank approximation

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