Fast prediction with sparse multikernel LS-SVR using multiple relevant time series and its application in avionics system

DOI10.1155/2015/460514zbMath1394.93357OpenAlexW1574875511WikidataQ59118640 ScholiaQ59118640MaRDI QIDQ1665732

Y. Aharonov

Publication date: 27 August 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/460514

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Least squares and related methods for stochastic control systems (93E24)

Uses Software

• SHOGUN

Cites Work

• Design of a multiple kernel learning algorithm for LS-SVM by convex programming
• Reduced rank kernel ridge regression
• Low rank updated LS-SVM classifiers for fast variable selection
• High performance optimization
• On Multiple Kernel Learning Methods
• SMO Algorithm for Least-Squares SVM Formulations
• Semidefinite Programming
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