A robust method based on LOVO functions for solving least squares problems

DOI10.1007/s10898-020-00970-4OpenAlexW3118754645MaRDI QIDQ2045017

R. Lopes, F. N. C. Sobral, Emerson Vitor Castelani, Wesley V. I. Shirabayashi

Publication date: 11 August 2021

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1911.13078

zbMATH Keywords

robust least squaresoutlier detectionLevenberg-Marquardtlow order-value optimization

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Least squares and related methods for stochastic control systems (93E24) Parallel numerical computation (65Y05) Artificial intelligence (68Txx)

Uses Software

• RAFF.jl

Cites Work

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• Low order-value approach for solving var-constrained optimization problems
• Continuous optimization methods for structure alignments
• Low order-value optimization and applications
• Optimality condition and complexity of order-value optimization problems and low order-value optimization problems
• Order-value optimization: formulation and solution by means of a primal Cauchy method
• Generalized order-value optimization
• Convergence and complexity analysis of a Levenberg-Marquardt algorithm for inverse problems
• A survey of outlier detection methodologies
• Nonlinear-programming reformulation of the order-value optimization problem
• Use of the Hough transformation to detect lines and curves in pictures
• Least Median of Squares Regression
• Detection of Influential Observation in Linear Regression
• A new curve detection method: Randomized Hough transform (RHT)