文件名称:The_Levenberg-Marquardt_Algorithm
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LM算法
老外写的The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method-The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method
老外写的The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method-The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method
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Levenberg-Marquardt算法求单应性矩阵
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Levenberg-Marquardt算法求单应性矩阵
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The_Levenberg-Marquardt_Algorithm.pdf