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说明： 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)
(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)
文件列表：
The_Levenberg-Marquardt_Algorithm.pdf
