The Kernel Conjugate Gradient Algorithms

Kernel methods have been successfully applied to nonlinear problems in machine learning and signal processing. Various kernel-based algorithms have been proposed over the last two decades. In this paper, we investigate the kernel conjugate gradient (KCG) algorithms in both batch and online modes. By...

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Vydané v:	IEEE transactions on signal processing Ročník 66; číslo 16; s. 4377 - 4387
Hlavní autori:	Zhang, Ming, Wang, Xiaojian, Chen, Xiaoming, Zhang, Anxue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 15.08.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive algorithms Algorithms Computational efficiency conjugate gradient algorithm Conjugates Convergence Criteria Hilbert space Iterative methods Kernel Machine learning Machine learning algorithms nonlinear processing online sparsification Optimization regularization Reproducing kernel Hilbert space Robustness (mathematics) Signal processing Signal processing algorithms
ISSN:	1053-587X, 1941-0476
On-line prístup:	Získať plný text
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