A majorization-minimization scheme forL2support vector regression

DOI10.1080/00949655.2021.1918691OpenAlexW3158867100MaRDI QIDQ3389658

Songfeng Zheng

Publication date: 23 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2021.1918691

zbMATH Keywords

quadratic programmingmajorization-minimization algorithmsupport vector regressionsquared \(\epsilon\)-insensitive loss function

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02) Statistics (62-XX)

Uses Software

• SVMlight
• LIBSVM

Cites Work

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• Asymmetric Least Squares Estimation and Testing
• Asymmetric least squares support vector machine classifiers
• Weighted least squares support vector machines: robustness and sparse approximation
• Advanced algorithms for penalized quantile and composite quantile regression
• Regression Quantiles
• 10.1162/15324430152748218
• Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning
• A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines
• Large scale kernel regression via linear programming

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