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Department of Mathematics,
Department of Mathematics,
University of California San Diego
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Math 278C - Optimization seminar and Data Science
Ruixue Zhao
Shanghai Jiaotong University
On a Global Complexity Bound of the Levenberg-Marquardt Method
Abstract:
In this paper, we propose a new updating rule of the Levenberg–Marquardt (LM) parameter for the LM method for nonlinear equations. We show that the global complexity bound of the new LM algorithm is $O(\epsilon^{-2})$, that is, it requires at most $O(\epsilon^{-2})$ iterations to derive the norm of the gradient of the merit function below the desired accuracy $\epsilon$.
Host: Jiawang Nie
November 1, 2017
4:00 PM
AP&M 2402
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