A Brief Description of the Levenberg-Marquardt Algorithm Implemented by levmar

By Manolis I. A. Lourakis. 2005

613 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a92844ea0726e0ebb3fdf99b070d1e8e289eb97f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters (2012, methodology): “As the solution approaches the minimum, damping parameter is adaptively decreased, the LMA approaches the Gauss-Newton algorithm, and the solution typically converges rapidly to the minimum [22,23].”
A Survey of Optimization Methods From a Machine Learning Perspective (2019, methodology): “If the L2 norm is used in the constraint function, it becomes the Levenberg-Marquardt algorithm [154].”
The Levenberg-Marquardt method for nonlinear least squares curve-fitting problems c © (2013, background): “In lm.m users may select one of three methods for inializing and updating λ and p. 1. λ0 = λo; λo is user-specified [5]. use eq’n (13) for hlm and eq’n (16) for ρ if ρi(h) > 4: p← p + h; λi+1 = max[λi/L↓, 10−7]; otherwise: λi+1 = min [λiL↑, 107]; 2. λ0 = λo max [ diag[JTWJ] ] ; λo is…”
A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement (2020, methodology): “In order to tune the weights and biases of ANN models, the Levenberg–Marquardt algorithm (LMA) was used as it is often the fastest BP algorithm in training [65, 82, 83].”
Bluetooth positioning using RSSI and triangulation methods (2013, background): “We put the mobile node at position (300,400), the distances between the mobile and the other reference nodes are equally 5 meters.”